Systems and methods for determining patient hospitalization risk and treating patients

Abstract

Systems and methods for determining patient hospitalization risk and treating patients are disclosed. The systems and methods may include: extracting patient data from one or more databases corresponding to a pool of patients with end-stage renal disease; using a predictive model that utilizes the extracted patient data to generate a corresponding expected probability of hospitalization within a predetermined time period for each of the patients; identifying a subset of patients with a higher corresponding expected probability than other patients in the pool of patients; identifying, for each patient, at least one factor from the patient data that increases the expected probability of hospitalization; and based on the identified factor, determining and performing a clinical intervention to reduce the probability of hospitalization within the subset of the pool of patients.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This is a non-disclosure filing of and claims the benefit of the filing date of co-pending U.S. Provisional Patent Application No. 62 / 637,332, filed on March 1, 2018, entitled “Systems and Methods for Determining Patient Hospitalization,” and is a non-disclosure filing of and claims the benefit of the filing date of co-pending U.S. Provisional Patent Application No. 62 / 716,034, filed on August 8, 2018, entitled “Systems and Methods for Determining Patient Hospitalization Risk,” the entire contents of which are expressly incorporated herein by reference. Technical Field

[0003] The present disclosure relates generally to systems, devices, and methods related to healthcare. Background Art

[0004] The traditional healthcare system is based on a fee-for-service model whereby healthcare providers are compensated on a per-treatment or per-service basis. Under this model, healthcare provider compensation increases as the number of treatments or services provided increases. Thus, there is no financial incentive for such providers to efficiently manage the number of services / procedures provided, nor is there any financial incentive tied to the overall health outcomes of patients. This traditional system has resulted in escalating healthcare costs and inefficiencies that hinder the quality of overall care for patients.

[0005] Furthermore, many patients—particularly those with chronic conditions—interact with a variety of different entities and health care professionals during the diagnosis, treatment, and long-term care management process, including hospitals, clinics, laboratories, pharmacies, physicians, clinicians, and / or other specialists. Patient treatment information may be scattered across multiple entities, repositories, and medical professionals, which may result in a lack of communication or poor communication between the various entities involved, which may adversely affect the patient's treatment and health, and may even cause life-threatening treatment conditions. Furthermore, this uncoordinated data processing and overall treatment of patients leads to inefficiencies that may lead to increased overall medical costs. In this regard, the traditional fee-for-service health care model is far from ideal in terms of both quality of care and economics. The latter is evidenced by the continued increase in health care costs in the United States that are difficult to sustain under the fee-for-service model.

[0006] With respect to these and other considerations, the present improvements may be useful. Summary of the invention

[0007] The present invention content is provided to introduce some concepts in a simplified form, and these concepts will be further described in the following detailed description. The present invention content is not intended to identify the key features or essential features of the present disclosure in fact. The present disclosure may include the following various aspects and embodiments.

[0008] According to one or more embodiments of the present disclosure, a method for determining the risk of hospitalization of a patient and treating the patient is disclosed. In one embodiment, the method includes: extracting patient data from one or more databases corresponding to a pool of patients with end-stage renal disease (ESRD); generating a corresponding expected probability of hospitalization within a predetermined time period for each patient in the pool of the patient using a predictive model using the extracted patient data; identifying a subset of the pool of the patient having a higher corresponding expected probability than other patients in the pool of the patient; identifying at least one factor from the patient data that increases the expected probability of hospitalization for each patient in the subset of the pool of the patient; and based on the identified factors, determining and performing clinical interventions to reduce the probability of hospitalization within the subset of the pool of the patient, wherein the clinical interventions include at least one of the following: (a) administering one or more dialysis treatments in addition to the patient's existing dialysis schedule, (b) extending the patient's dialysis treatment time, (c) adjusting the patient's target weight for the dialysis treatment, (d) adjusting the dialysate sodium concentration for the patient's dialysis treatment, and (e) adjusting the patient's blood pressure medication.

[0009] In this and other embodiments, the predictive model comprises a gradient boosting framework.

[0010] In this and other embodiments, the at least one factor is identified for each patient using Shapley Add-On Interpretation.

[0011] In this and other embodiments, the predetermined period of time is 7 days or less.

[0012] In this and other embodiments, the extracted patient data includes patient demographics, patient laboratory values, patient disposition data, or a comprehensive assessment of the patient, or a combination thereof.

[0013] In this and other embodiments, the patient's demographic data includes the patient's date of birth, the patient's date of first dialysis, the patient's gender, the patient's race, the patient's ethnicity, or the patient's marital status, or a combination thereof.

[0014] In this and other embodiments, the patient's laboratory value includes the patient's hemoglobin level, or the patient's albumin level, or a combination thereof.

[0015] In this and other embodiments, the patient's laboratory values ​​are provided as an average, maximum, minimum, value spike, value drop, or trend value, or a combination thereof, over a specified time period.

[0016] In this and other embodiments, the patient's treatment data includes the patient's vital signs, and wherein the patient's vital signs are provided as an average value, a maximum value, a minimum value, a value spike and a value drop, or a trend value, or a combination thereof, over a specified time period.

[0017] In this and other embodiments, the patient's comprehensive assessment includes the patient's recent hospitalization history, the patient's history of missed appointments, any patient notes or complaints, a nurse's or other medical professional's assessment, or any delivered medications, or a combination thereof.

[0018] In this and other embodiments, the predictive model is built based on data from other patients.

[0019] In this and other embodiments, the method further comprises generating a report that ranks the pool of patients according to their respective expected probabilities of hospitalization, wherein the report also provides the identified factors for each respective patient. In this and other embodiments, the method further comprises providing the generated report to one or more health care providers.

[0020] In this and other embodiments, the method further includes transmitting an automated alert to one or more healthcare providers based on the expected probability of hospitalization.

[0021] In this and other embodiments, the pool of patients is patients of an ESRD Seamless Care Organization (ESCO).

[0022] A system for determining the risk of hospitalization for a patient with end-stage renal disease (ESRD) is also disclosed. In one embodiment, the system includes an integrated care system configured to: extract patient data from one or more databases corresponding to a pool of patients with end-stage renal disease (ESRD); generate a corresponding expected probability of hospitalization within a predetermined time period for each patient in the pool of patients using a predictive model that utilizes the extracted patient data; identify a subset of the pool of patients that has a higher corresponding expected probability than other patients in the pool of patients; identify, for each patient in the subset of the pool of patients, at least one factor from the patient data that increases the expected probability of hospitalization; and generate a report that ranks the pool of patients according to the patients' corresponding expected probability of hospitalization, wherein the report also provides the identified factors for each corresponding patient.

[0023] In this and other embodiments, the predictive model comprises a gradient boosting framework.

[0024] In this and other embodiments, the integrated care system is configured to identify the at least one factor using a Shapley add-on interpretation for each patient.

[0025] In this and other embodiments, the predetermined period of time is 7 days or less.

[0026] In this and other embodiments, the extracted patient data includes patient demographics, patient laboratory values, patient disposition data, or a comprehensive assessment of the patient, or a combination thereof.

[0027] In this and other embodiments, the patient's demographic data includes the patient's date of birth, the patient's date of first dialysis, the patient's gender, the patient's race, the patient's ethnicity, or the patient's marital status, or a combination thereof.

[0028] In this and other embodiments, the patient's laboratory value includes the patient's hemoglobin level, or the patient's albumin level, or a combination thereof.

[0029] In this and other embodiments, the patient's laboratory values ​​are provided as an average, maximum, minimum, sum of value spikes, value declines, or trend values, or a combination thereof, over a specified time period.

[0030] In this and other embodiments, the patient's treatment data includes the patient's vital signs, and wherein the patient's vital signs are provided as an average value, a maximum value, a minimum value, a value spike and a value drop, or a trend value, or a combination thereof, over a specified time period.

[0031] In this and other embodiments, the patient's comprehensive assessment includes the patient's recent hospitalization history, the patient's history of missed appointments, any patient notes or complaints, a nurse's or other medical professional's assessment, or any delivered medications, or a combination thereof.

[0032] In this and other embodiments, the predictive model is built based on data from other patients.

[0033] Other features and aspects are described in further detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] As an example, embodiments of the disclosed method and apparatus will now be described with reference to the accompanying drawings, in which:

[0035] Figure 1A is a flow chart illustrating an exemplary embodiment of a method for determining hospitalization risk for an end-stage renal disease (ESRD) patient according to the present disclosure;

[0036] Figure 1B is a schematic diagram illustrating an exemplary embodiment of a report of identified patients at risk of hospitalization according to the present disclosure;

[0037] Figure 1C is a schematic diagram illustrating an exemplary embodiment of patient variables for determining hospitalization risk for an end-stage renal disease (ESRD) patient according to the present disclosure;

[0038] Figures 1D-1F is a flow chart illustrating an exemplary embodiment of a process for care coordination for a patient according to the present disclosure;

[0039] Figure 2A is a schematic diagram illustrating an exemplary embodiment of a system for providing coordinated health care according to the present disclosure;

[0040] Figure 2B is a schematic diagram illustrating one exemplary embodiment of a system for assessing and treating diseases including kidney disease according to the present disclosure;

[0041] Figure 3 is a block diagram illustrating an exemplary embodiment of an integrated care system according to the present disclosure;

[0042] Figure 4 is a block diagram illustrating an exemplary embodiment of an operating environment according to the present disclosure;

[0043] Figure 5 is a block diagram illustrating an exemplary embodiment of another operating environment according to the present disclosure;

[0044] Figure 6-10 is a schematic diagram illustrating an exemplary embodiment of components of a system for providing coordinated health care according to the present disclosure;

[0045] Fig.11 is a schematic diagram illustrating an exemplary embodiment of a care coordination component of a system for providing coordinated health care according to the present disclosure;

[0046] Fig.12 is a schematic diagram illustrating an exemplary embodiment of a dialysis machine according to the present disclosure;

[0047] Figures 13A-13B An exemplary embodiment of a dialysis system according to the present disclosure is shown;

[0048] Fig.14 is a schematic diagram illustrating another exemplary embodiment of a dialysis system according to the present disclosure; and

[0049] Fig.15 is a block diagram illustrating one exemplary embodiment of a computing architecture according to the present disclosure. DETAILED DESCRIPTION

[0050] The present embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which a number of exemplary embodiments are shown. However, the subject matter of the present disclosure may be embodied in many different forms and types of methods and devices for dialysis machines and other potential medical devices, diagnosis and treatment for various diseases, and should not be construed as being limited to the embodiments described herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and are intended to convey the scope of the subject matter to those skilled in the art. In the drawings, like reference numerals represent like elements throughout.

[0051] The exemplary embodiments described herein are suitable for implementing value-based care, which is an alternative to the fee-for-service health care model. Under a value-based health care system (also known as a "pay-for-performance" model), health care providers receive financial incentives related to the quality and efficiency of care and patient outcomes.

[0052] Some example embodiments are configured to provide coordinated care to a patient population with a chronic disease such as chronic kidney disease (CKD). CKD is a progressive disease characterized by decreased kidney function. Once kidney function drops below a threshold, the patient is considered to have kidney failure or end-stage renal disease (ESRD). ESRD is the final stage of CKD and requires dialysis treatment (without transplantation) for the rest of the patient's life.

[0053] In the United States, a model of value-based care that can implement the example embodiments described herein is the Comprehensive ESRD Care (CEC) model, which is a Accountable Care Organization (ACO) model developed under the authorization of the Center for Innovation in Medicare and Medicaid in the United States. In order to implement the CEC model, an ESRD Seamless Care Organization (ESCO) was formed. ESCO is an ACO formed by voluntarily coming together by health care suppliers and providers. The resulting ESCO is a legal entity that provides coordinated care for ESRD beneficiaries through the CEC model.

[0054] Under the ESCO model, the ESCO shares in the savings and losses incurred by the Centers for Medicare & Medicaid Services (CMS) for the ESCO’s beneficiaries. Savings or losses are determined by CMS based on a spending benchmark that is derived from a baseline that reflects historical spending data for similar or comparable beneficiaries. This benchmark is compared to actual Medicare fee-for-service (FFS) Part A and B spending for the participating patient population during the performance year. Savings are also adjusted based on quality performance. Any reduction in costs translates directly into increased shared savings (benefits) because expenses are measured against a predetermined benchmark. Quality of care is incentivized by applying a quality performance adjustment to the calculated shared savings.

[0055] The ESCO is responsible for the overall care of each patient, which goes beyond the scope of dialysis treatment. For example, if a patient is hospitalized for any reason (e.g., infection, vascular dialysis access complications, and / or cardiac complications), the hospitalization costs will be included in the annual savings calculation. Since hospitalization costs are particularly expensive, it is very beneficial for the ESCO to avoid patient hospitalization from a financial perspective. The example embodiments described herein implement a holistic approach to oversee and manage all aspects of patient health, which improves the quality of care while improving the efficiency of medical resources and overall cost efficiency.

[0056] Some example embodiments described herein analyze medical data of appropriate patient populations to intervene in high-risk patients to reduce the likelihood of hospitalization. Some examples analyze patient data to predict when a patient is likely to experience a specific health-related event or disease process stage and provide / adjust treatment accordingly.

[0057] According to an exemplary embodiment, patient information can be sent to a coordinated care system, managed in a coordinated care system and / or accessible by a coordinated care system, so that patients can receive high-quality, efficient, coordinated health care in a management system that can intelligently manage and coordinate the overall care of patients. The merged coordinated care system can, for example, replace fee-for-service care by providing value-based care to patients, thereby better controlling health care costs. For example, as described above, the patient population diagnosed with ESRD increases over time, typically caused by a variety of other diseases, including but not limited to diabetes, hypertension and / or glomerulonephritis. Due to the nature of the disease, patients with ESRD may face additional challenges. For example, necessary lifestyle changes may cause mental health to deteriorate. In addition, treatment at home may cause increased isolation from medical professionals. Along with the changes in the health care landscape, providing patients with the opportunity to coordinate resources for treatment may bring additional patient health benefits beyond dialysis treatment.

[0058] Although the exemplary embodiments described herein are related to kidney disease, it should be understood that the coordinated care system and infrastructure described herein can be substituted for kidney disease or applied to other chronic diseases in addition to kidney disease. As non-limiting examples, such other diseases can include cardiovascular-related diseases, lung, gastrointestinal, neurological, urological or gynecological diseases, diabetes, circulatory system diseases, Alzheimer's disease or other dementias, asthma, COPD, emphysema, cancer, obesity, smoking, cystic fibrosis or a combination thereof. In addition, although some examples are described with respect to kidney-related ACOs, such as implementation in ESCOs, it should be understood that the examples described herein can be similarly implemented in other ACOs with respect to other diseases or patient populations and / or any other suitable value-based health care model.

[0059] Exemplary embodiments according to the present disclosure may include a system for determining the risk of hospitalization for patients suffering from kidney disease (e.g., ESRD). As described below, the integrated care system may be configured so that data (e.g., laboratory test results) and recorded information (e.g., treatment notes) received from a clinic for ESRD patients undergoing dialysis treatment can be analyzed by one or more algorithms for determining the risk level of hospitalization for patients with kidney disease (e.g., ESRD). In some embodiments, the risk of a patient being hospitalized may be imminent (e.g., within seven days). It should be understood that, although seven days or a week are used in some exemplary embodiments, a patient's imminent hospitalization may occur approximately between 1 day and 15 days or within any predetermined amount of time, including but not limited to a month, three to six months, and the like. For example, the integrated care system may be configured to perform a method for determining a patient's risk of hospitalization and generating a report by analyzing selected patients for risk levels. For example, Figure 1A A flow chart of an exemplary method 100 for determining a patient's risk of hospitalization is illustrated. At step 105, data may be extracted. Data from a selected patient may be extracted by the integrated care system from other clinical systems, external systems, and / or other systems such as Figure 2A-11 Other database extractions shown in the figure.

[0060] As mentioned above, in Figure 1A At step 105, a number of variables may be extracted and / or assigned by the integrated care system, including but not limited to patient demographics, laboratory values, treatment data, and / or comprehensive evaluations. For example, Figure 1C An exemplary embodiment of an icon 140 of variables that may be included for determining a patient's risk of hospitalization is illustrated. Patient demographic data may include date of birth, date of first dialysis, gender, race, ethnicity, and marital status. Laboratory values ​​may be data including, but not limited to, hemoglobin, albumin, and the like. Additionally, laboratory data may be calculated in various ways, for example, to provide averages, maximums, minimums, value spikes and / or declines, and trend values ​​over a specified time period for analysis by the integrated care system.

[0061] It should be understood that the raw data variables can be transformable through feature engineering to create additional variables and / or features based on analysis of data patterns and clinical experience. Treatment data can include patient signs, such as blood pressure, weight, pulse, temperature, respiratory rate, etc. Treatment data can also be calculable in various ways, such as providing average values, maximum values, minimum values, value spikes and / or declines, and trend values ​​within a specified time period for analysis by an integrated care system. Similar to laboratory values, the raw data variables of treatment data can be transformable through feature engineering to create additional variables and / or features based on analysis of data patterns and clinical experience. For example, the maximum systolic blood pressure within 90 days can be calculated as the patient's treatment data.

[0062] It should be understood that any number and type of patient variables may be utilized, and Figure 1C The variables are exemplary embodiments. In some embodiments, variables associated with patient hospitalization may include a recent patient hospitalization history; an engineering feature associated with a patient's most recent treatment; a patient's laboratory values ​​for albumin level, hemoglobin level, and / or lymphocytes; a patient's vital signs measured during a most recent dialysis treatment, including but not limited to blood pressure, weight, and / or temperature; a history of missed appointments (e.g., a patient's missed appointments for a prescribed treatment and / or evaluation); and / or a patient's annotated and / or measured shortness of breath at a most recent dialysis treatment.

[0063] In embodiments, the treatment data may also include, for example, a nurse or other medical professional evaluation, medications delivered, and ancillary information (e.g., oxygen administered) via check boxes and / or text input. Comprehensive patient evaluations by physicians, clinicians, and / or dietitians over selected time periods (e.g., monthly, yearly) may also be utilized. It should be understood that the integrated care system may convert text inputs into specified features for inclusion and analysis in one or more algorithms.

[0064] Come back for reference Figure 1A , at step 110, as at step 105 with respect to Figure 1C The extracted patient data described can be processed by the integrated care system. The patient data for processing can be measured data, calculated data, written notes, etc. Some of the extracted data (e.g., measured data, calculated data) is numerical, and some (e.g., clinical notes) is text and / or graphics.

[0065] In some examples, at step 110, some or all of the patient data in the form of numerical data may be processed into a more suitable form for further analysis by the integrated care system. Such processing may include, for example, scaling and conversion. In some examples, such processing may include screening to ensure that the data is within a feasible range, so as to filter out or identify erroneous data. In some examples, some or all of the extracted numerical data remains in its original unmodified form through processing 110.

[0066] According to some embodiments, also at 110, the extracted data of the graph (e.g., handwritten clinical annotations) can be converted to text data before further analysis. In some examples, this is achieved by applying a convolutional neural network, but other suitable algorithms can be used instead of or in addition to this type of network.

[0067] The text data (including any text discerned from the graph as described above) can be processed using natural language processing techniques. These techniques may include, but are not limited to, word2vec, doc2vec, continuous bag of words, or others. This processed data can then be used to train a machine learning model to identify (e.g., predict) a specific outcome, whether the outcome is a hospitalization, a specific symptom, or other medically relevant variables.

[0068] In some embodiments, Figure 1C As illustrated at step 115 in the example of , the processed data (including any of the digital identifiers corresponding to the text data) can be sent to one or more algorithms of the integrated care system for analysis (e.g., prediction). In some examples, the algorithm can be used to learn from historical data (raw or pre-processor) and identify risks (e.g., make predictions) based on the historical data (raw or pre-processor). For example, the gradient boosting framework and / or the extreme gradient boosting tree algorithm can be utilized. Some examples implement XGBoost. At step 115, the algorithm can analyze the selected data to determine a risk score for hospitalization, for example, to identify risks. As described above, Figure 1C The patient data described in the can be used by the integrated care system to determine a risk score for each patient for possible hospitalization (e.g., immediate and / or long-term hospitalization). In some examples, an algorithm (e.g., a gradient boosting framework and / or an extreme gradient boosting tree algorithm) can analyze data for a particular patient in the context of corresponding data for a group of other patients.

[0069] In some examples, the analytical / predictive algorithm of the integrated care system may examine and analyze the entire pool of patients in order to assign each patient a corresponding risk score over a predetermined time period (e.g., 7 days, weeks, months, etc.). However, it should be noted that in some examples, the algorithm may be run for a single patient from the pool or any suitable number of selected patients.

[0070] At step 120, the document may be provided by a care analysis and guidance system (e.g., an integrated care system), by a care coordination system, and / or by a care navigation unit (see Figure 1A Step 125) can be generated. Now refer to Figure 1B , report 130 can be generated by an integrated care system for patients (e.g., ESRD patients) who have recently received dialysis treatment in a clinic, identifying those patients with a risk / probability of hospitalization and / or reasons associated with risk determination. In some embodiments, the report can indicate the risk score of the patient's hospitalization and / or the associated reasons for each patient. For example, patient John Doe can be determined by the integrated care system to be at risk of imminent hospitalization, with a calculated risk score of approximately 85.90%. The associated reasons identified by the integrated care system can include a recent hospitalization (e.g., John Doe has been hospitalized in the previous four days), and the patient is determined to be experiencing shortness of breath. It should be understood that John Doe's shortness of breath can be indicated by a medical professional's annotation at the time of dialysis treatment, and / or the integrated care system can have calculated shortness of breath based on patient signs measured at the time of dialysis treatment (e.g., blood oxygen level, heart rate, etc.). Report 130 can also include additional patients, e.g., Jane Doe, who are also at risk of hospitalization. For example, Jane Doe may have a calculated risk score of 85.06% for hospitalization (e.g., immediate and / or long-term) based on the medical professional notes and the prior eight days of hospitalization. The report 130 may include a list of patients associated with a physician, or clinic, or other medical professional or care provider.

[0071] In some examples, the causes or primary factors for risk determination are determined by using Shapley's additive interpretation technique such as described in "A Unified Approach to Interpreting Model Predictions" by Scott M. Lundberg et al. (2017), which is fully incorporated herein by reference. This allows for the determination of patient interventions that target factors that are most likely to affect the patient's expected probability of hospitalization.

[0072] In an embodiment, a report 130 may be generated such that patients are ranked according to their associated calculated risk scores. In this way, a care provider receiving the report may be alerted that the patient is at the highest risk. At step 125, the report 130 may be provided to a care coordination system and / or a care navigation unit so that medical professionals may contact the identified patient and determine appropriate interventions to help minimize or eliminate the risk of hospitalization (see Figures 1D-1F). For example, if the list of reasons indicates that the patient has a high temperature, the patient may have an infection. The care coordination system and / or care navigation unit can set up an appointment for the patient with their primary care physician for testing and evaluation (e.g., culture draw, follow-up temperature reading, etc.).

[0073] Reference now Figures 1D-1F , a flow chart 150 of an exemplary embodiment of a process for a care coordination system and / or care navigation unit for processing reports and patient follow-up is shown. For example, Figure 1D An exemplary process of coordinating patient care, such as by a technician, care coordinator, or other service provider, is illustrated. Providing additional care and coordination of patient services can minimize and / or eliminate a patient's risk of hospitalization, thereby avoiding additional health care costs and / or improving the patient's health.

[0074] At step 151, a report (e.g., report 130) may be accessed by a member of a care coordination system and / or a care navigation unit. In some embodiments, the report may be accessible to a technician, a care provider, a service provider, and / or another health care provider. At step 152, report 130 may be filtered and / or sorted to identify patients determined to be at risk for hospitalization, and a hospitalization risk score for each patient may be assessed at step 153.

[0075] At step 154, additional records may be evaluated to determine if the identified patient has been sent to an emergency room (ER), and steps 155, 156, 157 may determine if a hospitalization record and / or ER visit exists in the integrated care system, and if so, if the patient has only visited the ER, only been hospitalized, or an ER visit that resulted in hospitalization. If at step 156, the patient is determined to have been hospitalized, with or without a previous visit to the ER, then at step 158, hospitalization authorization may be confirmed and this information may be entered into the integrated care system for the patient. If at step 157 the patient visited the ER but was not hospitalized, then at steps 159 and 160, respectively, the patient may have been transferred from the ER to a clinic, or the patient may have been discharged from the ER and sent home. In the event that the patient is transferred to a clinic and / or discharged at steps 159 and 160, a note may be added to the report 130 at step 161 for a medical professional to follow up with the patient. In the event that the patient is not transferred to a clinic and / or discharged from the ER at steps 159 , 160 , the records in the integrated care system may be evaluated back at step 155 to determine the patient's status.

[0076] If no record of a hospitalization and / or ER visit exists in the integrated care system at step 155, the patient's record may be further evaluated at step 162 for recent activity and / or notes or other information that should be included in report 130. Additionally, if additional patient information has been included in report 130 at step 161, the additional information may also be included at step 162.

[0077] When all information has been added to the report 130, a member identified by the technician, care coordinator or service provider (e.g., a nurse, clinician, physician, care coordinator and / or other medical professional) at step 163 may contact the patient to discuss the patient's overall condition and any health concerns at step 164. If the patient does not appear, a callback call may be arranged at step 167. In some embodiments, if the patient is contacted by the technician, care coordinator or service provider, the care provider (e.g., a medical professional) may also be included in the conference call at step 165 for additional assistance. For example, a medical professional (e.g., a nurse, clinician, physician, specialist or the like) may be able to answer any medically relevant questions and / or provide additional medical information to address patient concerns. The technician, care coordinator or service provider may remain on call to provide any additional coordinated care, for example, if additional diagnostic tests need to be arranged, or other clinicians should be involved in the care of the patient determined by the medical professional. In some embodiments, at step 166, information (e.g., the patient's medical record) may be sent to the medical professional by the care coordinator via the care coordination system of the integrated care system so that the evaluation is separate from the patient discussion. The medical professional may be able to access the patient record through the integrated care system and notify the care coordinator of any additional information obtained from and / or provided for the patient.

[0078] Figure 1E An exemplary process for a care provider to coordinate patient care following step 165 is illustrated. For example, at step 168, the patient's overall health may be asked, and at step 169, the medical professional may specifically address the reasons listed for the patient on report 130. For example, the medical professional may access the listed reasons and ask questions directly about symptoms and / or other potential health concerns based on the listed reasons. At step 170, the patient may also be asked if they have any health concerns that have not been addressed. If the patient has no additional concerns, at step 171, the patient may be notified that their condition may continue to be monitored, and the patient may be encouraged to contact a care coordinator if their condition changes or requires additional assistance. It should be understood that at step 172, patient notes and other information from step 171 may be entered into the integrated care system.

[0079] If the patient does have additional concerns, then at step 173, the medical professional may be able to determine whether the health concerns are new conditions and / or worsening conditions, and whether the patient has discussed his concerns with his primary care physician or other specialists. At step 174, the medical professional may additionally determine whether the patient needs an immediate assessment. For example, the medical professional may determine that the patient should be assessed by his primary care physician, clinician, nephrologist, specialist or other medical professional for further assessment and testing. If the medical professional determines that the patient needs an immediate assessment, then at step 175, the patient may be notified that the appropriate parties are being notified, and other steps related to scheduling and coordination may be handled by the care coordinator. If the patient does not need an immediate assessment determined by the medical professional at step 174, then at step 176, the patient information may be sent to the appropriate parties (e.g., primary care physician, clinician, nephrologist, specialist or other medical professional) for additional assessment and potential follow-up. Contact information may also be provided to the patient at steps 175, 176, and the patient may be encouraged to contact the care coordinator if his condition changes or requires additional help. It should be appreciated that at step 172 , the patient notes and other information from steps 175 , 176 may be entered into the integrated care system. In some embodiments, at step 172 , the integrated care system may update the report 130 .

[0080] Figure 1F The invention illustrates exemplary embodiments of interactions and participation between various parties associated with the integrated care system. Fig.11 As described, the care coordination system and / or navigation unit may involve multiple parties in order to coordinate overall patient treatment. As described above, the technicians or service providers may include call personnel, operators, nurses, clinicians, physicians, care coordinators, and / or other medical professionals, and each may interact with the patient individually based on the report 130, and the report 130 may be updated based on their interactions with the patient. Once the report 130 has been updated as described in the flowchart 150, the report 130 may be provided to another party or service provider, such as a field nurse and / or a specialist nurse, including but not limited to a renal care nurse. Figure 1FAs shown, each party's swimming lane can define further patient interaction.For example, for example, the report 130 of the update from step 172 can be provided by a technician, a care coordinator or a service provider, and is sent to the responsible party at step 177.At step 178, a field nurse or other medical professional can receive the updated report, and determine which patients identified as being at risk of hospitalization are arranged to participate in treatment (for example, dialysis treatment at the clinic).At step 179, a field nurse can visit each identified patient participating in treatment to evaluate its condition and / or solve any patient concerns face to face.Additionally and / or alternatively, at step 180, a specialist nurse (for example, a renal care nurse) can check the report 130, and determine whether the care navigation unit has contacted the identified patient, and at step 181, staff or other medical professionals can be assigned to find and contact patients so as to directly evaluate patients.For example, face-to-face contact between a patient and a medical professional can allow diagnosis and / or evaluation that cannot otherwise be determined by report 130.This additional follow-up and care can help reduce and / or eliminate the patient's risk of hospitalization, which can be beneficial to the patient's long-term care. At step 182, the technician, care coordinator, or service provider can determine whether any patients missed scheduled treatments, and if so, if they were hospitalized. Additional follow-up and patient contact can then be coordinated.

[0081] The report 130 can be generated by the integrated care system to identify and / or provide intervention treatment for patients. In some embodiments, when the report is generated, one or more patients who can benefit from the predetermined treatment can be identified based on the risk score level. The care provider can evaluate the identified patients based on the report 130 to guide additional and / or different treatments. For example, additional services and / or treatments that can change the course of their disease can be provided for the identified patients with high risk scores. In some patients, the kidney disease process can be slowed or even reversed by receiving immediate intervention treatment, thereby potentially minimizing or even preventing future imminent hospitalization. The integrated care system can determine the risk of hospitalization for one or more patients, which can cause the patient to receive additional services and care in a proactive manner, potentially preventing the deterioration of their kidney disease or even hospitalization.

[0082] refer to Figure 2A, according to an example of the present disclosure includes a coordinated care framework 200 for treating a patient or patient population 240. The overall care of the patient / population 240 is overseen and coordinated by a care coordination system 210. The care coordination system 210 includes a care analytics and guidance system 220 (which is interchangeably referred to herein as an "integrated care system") that receives, analyzes, and creates data for coordinating the care of the patient / population 240. The care coordination system 210 utilizes a care navigation unit (CNU) 230 that implements coordinated care based on data received from the care analytics and guidance system 220. To manage the overall health and well-being of the patient / population 240, the care coordination system 210 communicates with a number of related entities and components. In Figure 2A In the diagram, double-arrow lines graphically represent communication and interaction flows / channels.

[0083] exist Figure 2A In the example shown, the care coordination system 210 coordinates care for a patient 240 between entities including a chronic care center or clinic 241, physicians 242 (who may include a nephrologist, particularly for kidney patients), nurses 243, laboratories 244 (e.g., a blood lab or other diagnostic lab), a pharmacy 245, a hospital 246, medical equipment 247 (e.g., a dialysis machine or other medical treatment / monitoring equipment), an urgent care clinic 248, specialty services 249, counseling and mental health services 250, nutritionists / dietitians 251, transportation services 252, medical equipment and supply providers 253, an ambulatory surgical center (ASC) 254, additional services 255, medical records 256, financial and billing records 257, and a payer 258 (e.g., CMS or a private insurance company).

[0084] It should be understood that some example embodiments may include other entities not shown, and / or may exclude some of the entities shown. Furthermore, it should be understood that the communication channels shown are not exclusive, and that the various entities may also communicate directly or indirectly between each other and / or the patient 240 as appropriate. In some examples, communication between the care coordination system 210 and one or more of the other entities may be indirect, passing through one or more intermediate entities. For example, the coordination of the nurse 243 may be conducted directly between the care coordination system 210 and the nurse 243, or via an intermediate channel such as the clinic 241, 248, the hospital 246, or any other suitable channel.

[0085] According to some examples, Figure 2AThe framework 200 can be used to treat diseases such as the progression of kidney disease, such as end-stage renal disease (ESRD) and / or chronic kidney disease (CKD). Patients with ESRD are patients who are receiving long-term care for kidney disease, such as dialysis treatment. If kidney treatment is not properly maintained, patients with kidney disease (e.g., ESRD) will be hospitalized, but some hospitalization events will be disruptive and expensive to patients, and are often prevented by intervention. For example, the integrated care system 220 can be used and / or configured to identify patients at risk and the reasons for being identified as being at risk to determine the patient's risk of hospitalization. Monitoring the health status trends of dialysis patients may bring challenges. For example, patients may show varying degrees and unstable degrees of functional / cognitive impairment, and may be accompanied by complex clinical abnormalities, regardless of the length of the patient's dialysis time. By determining the patient's risk of hospitalization, the integrated care system can identify additional and / or different treatment options for the patient. According to an exemplary embodiment of the present disclosure, including a coordinated care framework 200 of a care analysis and guidance system 220, patients can delay and / or completely avoid hospitalization by receiving immediate intervention treatment to potentially slow down or reverse the disease process.

[0086] The care analysis and guidance system (integrated care system) 220 may include and execute various models and / or programs related to health care. In some examples, these models and / or programs are specifically used to implement or execute specific value-based care frameworks (e.g., ESCO models, other ACO models, chronic special needs plans (C-SNP's), etc.), while other examples may include models / programs that are generally applicable to multiple value-based care frameworks. It should also be understood that other types of value-based care models can be provided for other chronic diseases, including but not limited to chronic kidney disease, or one or more of the above-mentioned other chronic diseases and conditions. These health care models may affect the way to improve the value-based care provided to patients, such as by more effectively managing the care of patients within a specified structure, and may replace the traditional fee-for-service (FFS) model. The fee-for-service model may generally focus on the quantity rather than the quality of personalized patient care, and there is little motivation to improve the overall health of patients. Compared with the value-based model, this model may be less efficient and less effective.

[0087] Patient care is shifted from the traditional fee-for-service model to a value-based health care model that may improve the care received by patients, reduce total costs, and may improve the management of a large number of patient populations diagnosed with the same chronic disease. For example, as described above, the value-based health care model can pay providers based on the quality of care received by patients (e.g., clinical treatment effects, meeting specific performance criteria, etc.), and providers and patients can benefit from being committed to solving and improving the overall health of patients. For example, CMS can set a budget for patient care of a diagnosed disease (e.g., ESRD), thereby stimulating health care providers to innovate to reduce the cost of providing the treatment of the disease. In some embodiments, payment can be associated or negotiated by a "risk-sharing" contract, wherein the cost associated with the coordinated care of the disease and the patient and the savings are borne jointly by providers and payers. This arrangement exists in the ESCO model described in more detail above.

[0088] In some embodiments, the care coordination system can identify, test and / or evaluate innovations through the CEC / ESCO framework to improve patient care for medical insurance beneficiaries diagnosed with ESRD. The care coordination system can provide structure for dialysis clinics, nephrologists or other experts and / or other providers to be contacted with each other, so that consistent beneficiaries can carry out care coordination. Value-based health care models may motivate providers based on the quality of delivered care services. For example, the care coordination system may include incentives for improving care coordination, personalized patient care and / or improving the long-term health outcomes of patient populations. The care coordination system can also coordinate the treatment effects measured by medical insurance Part A (e.g., hospital insurance) and Part B (e.g., medical insurance) expenditures, including expenditures related to dialysis services for its consistent ESRD beneficiaries, such as clinical quality, finance, etc. It should be understood that some value-based health care models may also include medical insurance Part D (e.g., prescription drug insurance) expenditures.

[0089] The integrated care system 220 can form part of a clinical system for diagnosing and treating patients in all aspects of care. The integrated care system 220 can be connected to other clinical systems, including but not limited to pharmacies, CKD / ESRD data registries, etc. For example, the integrated care system can automatically send prescriptions and other patient information to the pharmacy based on information provided by medical professionals, and can send and receive data and information to the CKD / ESRD data registry to compare with other patients and predict future treatments. The integrated care system can determine events associated with CKD / ESRD and take appropriate measures, including but not limited to notifying patients, notifying clinicians when specific interventions are needed, and / or reminding clinicians of upcoming important intervention dates.

[0090] One or more external systems or external systems may also be connected to the integrated care system 220. For example, the external systems may include one or more of diagnostic and / or treatment equipment (such as a dialysis machine), a laboratory, a doctor's office, a hospital, and / or electronic medical records. Patient information may be sent and received between the integrated care system and the external systems so that patient care may be more efficient, standardized, and consistent across multiple functions. For example, the integrated care system 220 (see Figure 2A ) can receive information from the patient's electronic medical record, thereby accessing historical information. Dialysis units or dialysis machines, physician offices, laboratories, and hospitals can send information to and receive information from the integrated care system based on patient treatment.

[0091] As follows about Figure 12-15 As described, in some embodiments, the care coordination system can provide information to the dialysis machines 1200, 1300, 1400 for use in dialysis treatment. In some embodiments, the integrated care system can send prescriptions from medical professionals for prescribing dialysis treatment to the dialysis machines 1200, 1300, 1400, in which case the integrated care system can receive prescriptions from doctors' offices or hospitals. The integrated care system can also verify the prescribed treatment against the patient's laboratory tests or medical records, and in some cases, the prescription can be remotely programmed into the patient's dialysis machine, or the prescription can be forwarded to the machine for local settings. In this way, it can be ensured that the patient receives the necessary and correct treatment, and the patient can be prevented from receiving or receiving an inappropriate amount of dialysis treatment, thereby reducing human error and improving patient care. The integrated care system 220 is also capable of notifying relevant medical professionals based on information received from these external systems and other clinical systems, for example, to provide the patient with appropriate medical treatment, including the process (one or more) of the treatment that can reduce or avoid the risk of hospitalization or even change the patient's disease course. The progression of a patient's kidney disease may be slowed and / or even reversed if the patient receives proactive medical management.

[0092] Figure 2B is another illustration of the coordinated care framework. Figure 2B The coordinated care framework 200' and Figure 2A The coordinated care framework 200 of the embodiment shares features described herein unless otherwise noted. The coordinated care framework 200' described in this example is provided for integrating patient care in treating renal diseases, for example, ESRD and / or CKD are shown (although it can also be adapted for treating similar Figure 2AThe framework may be applicable to other chronic diseases). The care coordination system 210' may coordinate at least some aspects of patient care with the integrated care system 220' (which may include and execute health care-related models and / or programs 260) to support patient care. Various components may participate in the care coordination system 210' to provide complete patient care via the care framework. For example, any number of incorporated care components may send information to the integrated care system 220' and receive information from the integrated care system 220', including but not limited to ancillary services components 265, data creation and / or management components 270, care provider components 275, equipment and / or supplies components 280, and regulatory components 285. In some embodiments, the care coordination system 210' may collaborate with third-party resources including but not limited to laboratory services, research, etc. In some embodiments, the care framework may include, be implemented by, or be associated with a care navigation unit 230'. In Figure 2B In the example of FIG. 2 , it is noted that the care navigation unit 230 ′ is indicated as a separate entity from the care coordination system 210 ′, but it should be understood that in other examples (e.g., see Figure 2A ), the care navigation unit can be included as part of the care coordination system.

[0093] As described above, each component of the integrated care system (eg, care analysis and guidance system) 220, 220' may include one or more units, including internal services and support and external services and support. Figure 6 As shown in , the auxiliary service component 265 may include any number of "n" services 605a, 605b, ..., 605n related to auxiliary patient services. For example, the auxiliary service may include a laboratory 605a, a personalized care 605b, and / or a pharmacy 605c. Each of the auxiliary services 605a, 605b, ..., 605n can send and receive patient information to the integrated care system 220, 220' for compilation and analysis. For example, the laboratory can automatically send the results of the patient's blood test and other test results to the integrated care system 220, 220'. In addition, the integrated care system 220, 220' can automatically send a test instruction to the laboratory to perform a selected test on the patient sample based on the determination from the medical professional and / or other information collected by the care coordination system 210' via the care framework. Similarly, the integrated care system 220, 220' can automatically send a prescription and dosage instruction to the pharmacy based on the patient's test results and other factors determined by the integrated care system 220, 220'. The pharmacy may also send information related to other patient prescriptions to the integrated care system 220, 220' for potential adverse drug interactions, how to timely refill prescriptions, and / or patient-pharmacist interactions, etc.

[0094] In some embodiments, patients can benefit from the care of nutritionists and / or dietitians 605d to adjust dietary restrictions as an integral part of their care. For example, ESRD patients may have prescribed dietary requirements as part of receiving hemodialysis and other treatments for their kidney disease. Patients may benefit from the consultation of nutritionists and / or dietitians to move toward a healthier dietary lifestyle and other potential health-related benefits. Fluid management 605e can also be managed for patients to ensure that the patient is receiving the appropriate amount and type of fluid. Patients with CKD and / or ESRD may have fluid restrictions to obtain better dialysis results. Some patients may have difficulty understanding fluid intake, and / or may not be able to reliably track their fluid intake. In some embodiments, fluid management can be managed by nutritionists and / or dietitians, although it should be understood that in other embodiments, the patient's fluid intake can be managed by another medical professional. In an embodiment, a patient can benefit from the care of a mental health professional 605f, for example, a psychologist, a psychiatrist and / or other consulting services. As described above, the patient's mental health may be affected by the course of the disease, otherwise it may be ignored by other medical professionals during the treatment process. Therefore, arranging and providing a mental health professional may improve the patient's overall health.

[0095] Reference now Figure 7 As described above, the data creation / management component 270 may include one or more units related to the creation and / or management of patient data, including internal services and support and external services and support. For example, the data creation / management component 270 may include any number "n" of services 705a, 705b, ..., 705n. Figure 7 As shown, the electronic medical record (EMR) 705a, the data registry 705b and the clinical information 705c can receive, store and / or transmit the patient data record determined by the nursing analysis and guidance system 220, 220'. For example, the patient's medical record can be automatically updated after receiving the laboratory results, treatment information and / or notes from the medical professional. The nursing analysis and guidance system 220, 220' can utilize the patient's medical record for trends or trigger events so that the care coordination system 210' can provide relevant information to the medical professional for treatment and other care selection recommendations and for scheduling and coordinating various possible interventions. In some embodiments, the nursing analysis and guidance system 220, 220' can analyze multiple patients as part of the data registry for determining global trends and analyzing data from a macro level.

[0096] Figure 8An exemplary care provider component 275 is shown, including one or more units that provide patient care, as shown by reference numerals 805a, 805b, and 805n. Any number of "n" units may be included in the provider component 275. In some embodiments, the care provider may include a physician and / or physician group 805a (e.g., a primary care physician (PCP) and a specialist, such as a nephrologist), a practice management system 805b, a hospital 805c, and / or a clinic / center 805d, although additional or alternative care providers may also be envisioned. The integrated care system 220, 220' can send information to and receive information from the care provider for patient treatment. For example, the integrated care system 220, 220' can receive physician notes for patient examinations, hospitalization information, etc., and can send calculated information and other determined factors based on other patient data received. For example, the integrated care system 220, 220' may send estimates and treatment recommendations to identify, reduce, avoid and / or eliminate a patient's risk for aspects and / or effects of kidney disease or kidney disease treatments to provide treatment to the patient based on all received patient data and evaluations thereof.

[0097] Fig. 9 An exemplary equipment and / or supplies component 280 for a single patient is shown, for example, treatment supplies, which may include any number of "n" services 905a, 905b, ..., 905n. In some embodiments, the integrated care system 220, 220' can send and receive information related to a kit of disposable medical equipment 905a, information technology (IT) technical support 905b, inventory control 905c and / or dialysis units 905d, or dialysis machines in a clinic. As described above, many patients receive treatment at home, such as home dialysis, requiring a continuous supply of disposable medical supplies for each treatment. The delivery of supplies and / or dialysis equipment can be automatically monitored, replenished and / or stored by the integrated care system 220, 220' to ensure proper machine function and a stable supply of materials and resources to ensure that the patient receives all prescribed treatments.

[0098] Fig.10An exemplary regulatory component 285 is shown, which may include any number "n" of services 1005a, 1005b, ..., 1005n related to government and regulatory requirements. For example, certain state and federal regulations and regulatory agencies may be involved in insurance and / or Medicaid and the Centers for Medicare Services (CMS) 1005a, public product approval (e.g., the Food and Drug Administration (FDA)) 1005b, and billing 1005c. The integrated care system 220, 220' may send information to each of these units and receive information from each of these units to ensure proper billing coding, regulatory approval, and / or insurance payment.

[0099] As described above, the care navigation unit 230, 230' can oversee and coordinate patient care based on analysis and calculations determined by the integrated care system 220, 220' based on data and information from any of the components 265, 270, 275, 280, 285 and the care coordination system 210'. For example, the care navigation unit 230' can coordinate care for the patient to track the completion of intervention treatments to address functional and / or cognitive patient impairments over time, improve comorbidity management, and help drive high-value care selection and timing of treatment decisions for the patient over time. Fig.11 As shown, the care navigation unit 230, 230' can include different aspects of health care coordination indicated by reference numerals 1105a, 1105b, ..., 1105n, including but not limited to consultation, treatment transition, scheduling, patient monitoring, tracking, transportation and / or discharge care. For example, the integrated care system 220, 220' can determine that the patient needs transportation to and from the treatment center, and can automatically arrange transportation, such as public transportation, carpooling, taxi, riding a shared bike, etc., so that the patient does not miss the scheduled treatment. Additionally, the integrated care system 220, 220' can send patient results to relevant care providers, such as medical experts, doctors and / or nurses, for monitoring and / or treatment recommendations. The care navigation unit 230' can provide services to patients to address the complete health care needs related to their kidney disease.

[0100] The care navigation unit 230, 230' may include a treatment transition 1105b to enable the integrated care system 220, 220' to coordinate patient care over the course of a renal disease. For example, a patient may initially be diagnosed with chronic kidney disease (CKD). However, over time, without an intervention treatment (e.g., a kidney transplant) or improved renal function, the patient may develop end-stage renal disease (ESRD). As the patient's renal disease progresses, the patient may require additional services, support, and / or health care, which may be supervised and / or managed by the care navigation unit 230' via the integrated care system 220, 220' and through the care framework of the care coordination system 210, 210' under the care framework 200'. As described above, the care navigation unit 230, 230' may provide additional services and / or treatments to the patient through the care framework based on an associated hospitalization risk score. For example, to reduce the risk of hospitalization, the care navigation unit 230, 230' may evaluate the patient's condition based on patient parameters provided to the integrated care system 220, 220' (e.g., see Figures 1D-1F ). If necessary, the care navigation unit 230, 230' can then determine intervention treatments to reduce the hospitalization risk score. By proactively addressing potential patient health concerns, hospitalization can be delayed and / or avoided, and the patient's disease progression can be slowed or reversed.

[0101] Reference now Figure 3 , an integrated care system, such as integrated care system 220, 220', may include a controller 305, a processor 310, and a memory 320. The controller 305 may automatically control signals received and sent to other systems, such as additional clinical systems, external systems, and business management and billing systems. Communication between the controller 305 and other systems may be bidirectional, whereby the system may confirm control signals, and / or may provide information associated with the system and / or the requested operation. Additionally, a user input interface 315 and a display 302 may be configured to receive and / or display input from a user, such as a patient or a medical professional such as a doctor, nurse, technician, etc. Examples of components that may be employed within the user input interface 315 include a keypad, a button, a microphone, a touch screen, a gesture recognition device, a display screen, and a speaker. In some embodiments, the integrated care system 220, 220' may be a server, computer, or other device for storing and processing data and controlling signals to other systems. A power supply 325 may allow the integrated care system 220, 220' to receive power, and in some embodiments may be an independent power supply.

[0102] The processor 310 can be configured to execute an operating system that can provide platform services to application software, for example, for operating the integrated care system 220, 220'. These platform services can include inter-process and network communications, file system management, and standard database operations. One or more of many operating systems can be used, and the examples are not limited to any specific operating system or operating system features. In some examples, the processor 310 can be configured to execute a real-time operating system (RTOS), such as RTLinux, or a non-real-time operating system, such as BSD or GNU / Linux. According to various examples, the processor 310 can be a commercially available processor, such as a processor manufactured by INTEL, AMD, MOTOROLA, and FREESCALE. However, the processor 310 can be any type of processor, multiprocessor, or controller, whether commercially available or specially manufactured. For example, according to one example, the processor 310 can include an MPC823 microprocessor manufactured by MOTOROLA.

[0103] Memory 320 may include a computer-readable and writable non-volatile data storage medium configured to store non-transient instructions and data. Additionally, memory 320 may include a processor memory that stores data during operation of processor 310. In some examples, processor memory includes a relatively high-performance, volatile, random access memory, such as a dynamic random access memory (DRAM), a static random access memory (SRAM), or a synchronous DRAM. However, processor memory may include any device for storing data, such as a non-volatile memory, that has sufficient information throughput and storage capacity to support the functions described herein. Furthermore, examples are not limited to a particular memory, memory system, or data storage system.

[0104] The instructions stored on the memory 320 may include executable programs or other codes that can be executed by the processor 310. The instructions may be persistently stored as coded signals, and the instructions may cause the processor 310 to perform the functions described herein. The memory 320 may include information recorded on or in a medium, and the information may be processed by the processor 310 during the execution of the instructions. The memory 320 may also include, for example, data records, timing for treatment and / or operation, historical information, statistical information, and information databases for treatment. The database may be stored in the memory 320 of the integrated care system 220, 220' and may be accessed by the processor 310 and the controller 305. For example, historical data of patient information may be extracted from various databases in the integrated system 220, 220', including but not limited to patient laboratory results, treatment data, technician data (nurse notes) during treatment, etc. The extracted data may be used to generate a database that can be used to train a machine learning model to evaluate factors that lead to hospitalization of a patient. For example, a machine learning model may identify patients who have been hospitalized, and analyze patient laboratory values, treatment data, nurse notes, etc. for commonalities that may have led to hospitalization. The medium may be, for example, an optical disk, a magnetic disk, or flash memory, among others, and may be permanently affixed to the controller 305 or removable from the controller 305 .

[0105] The integrated care system 220, 220' may include a communication link 306 so that other systems can connect to the integrated care system 220, 220'. For example, additional clinical systems, external systems, and business management and billing systems can connect to the integrated care system 220, 220' to send and receive data and information associated with providing patient care. In some embodiments, the communication link 306 can be wireless so that the system can be remote, or one or more of the integrated care system 220, 220' and / or systems 265, 270, 275, 280, 285, 230' can reside and operate in a cloud-based architecture.

[0106] One or more algorithms may utilize models of historical data to analyze current patient data as it is input and / or collected by the integrated care system 220, 220'. The algorithms may analyze the patient data based on the historical data to determine the patients most likely to be hospitalized. The integrated care system 220, 220' may further generate a report identifying the patients determined to be most likely to be at risk of hospitalization. Such reports may be sent to the care coordination unit 125 for follow-up and treatment recommendations (see Figures 1A-1F ). This can allow medical professionals time to intervene and address a patient’s potentially heightened health concerns, which can ultimately reduce or avoid the risk of hospitalization. Timely intervention can slow or even reverse a patient’s kidney disease progression.

[0107] The integrated care system 220, 220' may also be wirelessly connected via antenna 345 for remote communication. For example, the integrated care system 220, 220' may determine one or more patient parameters through the controller 305, the processor 310 and / or the memory 320, and may access other patient parameters stored by an external system, for example, patient parameters stored on a server or database at a location away from the system or machine or in an electronic medical record from laboratory or hospital information. It may be advantageous for the integrated care system 220, 220' to access patient parameters that may otherwise be unknown or undetermined to provide a complete care analysis for the patient. As described above, patient data may be sent to and / or accessed by the integrated care system 220, 220'. The controller 305, the processor 310 and the memory 320 may receive, store and / or determine relevant demographic and laboratory values ​​or other data for calculation. The integrated care system 220, 220' may then use calculations to determine the risk of hospitalization. In some embodiments, when patient parameter information is updated, for example, new data points may be included in the system, and corresponding future or identified patient parameters may be updated and adjusted accordingly. In embodiments, any number of variables may be extracted for determining a patient's risk of hospitalization, for example, an upcoming hospitalization, or a hospitalization within a week or some other defined time window. In some embodiments, the integrated care system 220, 220' may utilize patient variables for determining a risk of long-term hospitalization, for example, within the next twelve months. Additionally, annotations (e.g., from medical professionals) may be included when determining a patient's risk of hospitalization. One or more algorithms may generate a risk score for hospitalization based on the extracted variables and historical data, and in some embodiments, may identify the primary factors associated with the generated risk score. As described above, by determining a patient's risk of hospitalization and causes, medical professionals may be able to develop personalized patient interventions to reduce risk and / or prevent hospitalization.

[0108] Reference now Figure 4-5 , describes an exemplary embodiment of an operating environment for a health care system (eg, coordinated care framework 200 , 200 ′) including an integrated care system (care analysis and guidance system) 220 , 220 ′. Figure 4 An example of an operating environment 400 that may represent some embodiments is shown. Figure 4As shown, operating environment 400 may include system 405 operable to treat a patient, such as a patient with a chronic disease. In various embodiments, system 405 may include computing device 410. Computing device 410 may include processing circuitry 420, memory unit 430, transceiver 450, and / or display 452. Processing circuitry 420 may be communicatively coupled to memory unit 430, transceiver 450, and / or display 452. It should be understood that in some embodiments, system 405 may include coordinated care framework 200, 200', and in some embodiments, system 405 may include other systems and / or frameworks.

[0109] In some embodiments, computing device 410 may be connected to network 460 via transceiver 450. Network 460 may include nodes 462a-n, such as remote computing devices, data sources 464, and / or the like.

[0110] Processing circuitry 420 may include and / or have access to various logic devices to perform processing according to some embodiments. Processing circuitry 120 or portions thereof may be implemented in hardware, software, or a combination thereof. As used herein, the terms "logic device," "component," "layer," "system," "circuit," "decoder," "encoder," and / or "module" are intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution, examples of which are represented by Fig.15 An exemplary computing architecture 1500 is provided. For example, logic, circuits, or layers may be and / or may include, but are not limited to, a process running on a processor, a processor, a hard drive, multiple storage drives (of optical and / or magnetic storage media), an object, an executable file, an execution thread, a program, a computer, a hardware circuit, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device (PLD), a digital signal processor (DSP), a field programmable gate array (FPGA), a system on a chip (SoC), a memory cell, a logic gate, a register, a semiconductor device, a chip, a microchip, a chipset, a software component, a program, an application, firmware, a software module, computer code, a combination of any of the foregoing, and / or the like.

[0111] It should also be appreciated that components of processing circuitry 420 may be located within an accelerator, a processor core, an interface, a separate processor die, fully implemented as a software application, and / or the like.

[0112] The memory unit 430 may include various types of computer-readable storage media and / or systems in the form of one or more higher speed memory units, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), double data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory, such as ferroelectric polymer memory, Osram memory, phase change or ferroelectric memory, silicon oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical cards, arrays of devices such as redundant array of independent disks (RAID) drives, solid-state memory devices (e.g., USB memory, solid-state drive (SSD)), and any other type of storage medium suitable for storing information. In addition, memory unit 430 may include various types of computer-readable storage media in the form of one or more lower-speed memory units, including an internal (or external) hard disk drive (HDD), a magnetic floppy disk drive (FDD), an optical disk drive that reads or writes from a removable optical disk (e.g., a CD-ROM or DVD), a solid-state drive (SSD), and / or the like.

[0113] The memory unit 430 may store various information, such as one or more programs to perform various functions for identifying and treating patients with CKD and / or ESRD. In some embodiments, the memory 430 may include logic with an application programming interface (API) and / or a graphical user interface (GUI) to read, write, and / or otherwise access information, such as via a display 452, a web interface, a mobile application ("mobile application", "mobile app" or "app"), and / or the like. In this way, in some embodiments, an operator can search, visualize, read, add, or otherwise access information associated with a patient population for use in identifying and treating CKD and / or ESRD.

[0114] In some embodiments, the memory unit 430 can store various information associated with the patient population for identification and treatment of CKD and / or ESRD. In some embodiments, the information stored in the memory unit 430 can be retrieved from and / or moved to a data source 464, including but not limited to a hospital information management system (HIMS), a laboratory information management system (LIMS), a health information system (HIS), an electronic medical record (EMR), a clinical trial database, and / or the like. For example, as a patient information analysis 435, one or more imaging or algorithms or a combination thereof may be implementable. In some embodiments, a program and / or algorithm can be used to determine a risk score for hospitalization.

[0115] Figure 5 An example of an operating environment 500 that may represent some embodiments is shown. Figure 5 As shown, operating environment 500 may include platform 505, for example, a health care exchange platform. In some embodiments, platform 505 may be used to provide an exchange of clinical data and / or clinical trial information between interested entities. In various embodiments, platform 505 may include an application platform operable to utilize services to identify patient populations and handle CKD and / or ESRD between nodes 560a-n and 570a-n. In an exemplary embodiment, platform 505 may be a software platform, suite, protocol set, and / or the like provided to a client by a manufacturer and / or developer ("developer") associated with medical equipment, health care services, clinical research services, laboratory services, clinical trial services, and / or the like.

[0116] For example, a developer may provide platform 505 as a data exchange interface for use by various entities, including government entities (e.g., FDA) and other stakeholders (e.g., drug manufacturers, medical device manufacturers, and / or the like). Entities such as hospitals, dialysis clinics, health care providers, government entities, regulatory entities, drug manufacturers, medical device manufacturers, and / or the like that provide and / or receive clinical trial services via developer-provided nodes 570a-n may use platform 505 to implement processes in accordance with some embodiments. Other entities may access platform 505 via a GUI such as a client application, a web interface, a mobile application, and / or the like, for example, to perform functions associated with memory 522. In some embodiments, at least a portion of platform 505 may be hosted in a cloud computing environment.

[0117] Nodes 570a-n may be data producers for memory 522, while nodes 560a-n may be data consumers for memory 522. For example, nodes 570a-n may include entities that provide clinical data, model information, and / or the like used by memory 522 to generate, execute, and / or evaluate patient populations. Nodes 560a-n may include third-party applications, decision makers, analytical processes, regulators, and / or other data consumers that may be interested in generating, executing, and / or evaluating results for patient populations. An entity may be both a data producer and a data consumer.

[0118] For example, node 560a may be a care provider (node ​​560b) that provides treatment to a patient based on an analysis of a patient population including medical records, laboratory data, pharmacies, etc. (node ​​570a). Data producers 570a-n may provide analytical data to platform 505, for example, in the form of records in a HIMS, LIMS, EMR, and / or the like, in accordance with a license. Data consumers 560a-n may access analytical data via platform 505 (e.g., through a HIMS, LIMS, EMR, and / or the like and / or a local copy of such records), in accordance with a license.

[0119] In some embodiments, platform 505 can operate according to a cloud-based model and / or an "as a service" model. In this manner, platform 505 can provide a service that operates as a single central platform that allows entities to access clinical data, model information, simulation results, and / or the like.

[0120] In some embodiments, one of the recommended treatments and / or services may be a change or modification of the dialysis treatment prescription for the patient. Figure 12-14 As shown and described below, dialysis machines 1200, 1300, 1400, such as dialysis machines such as peritoneal dialysis machines or hemodialysis machines, can be connected to integrated care systems 220, 220' for sending and receiving dialysis information to provide appropriate care to patients. The hemodialysis machine can be located in a renal clinic such as a renal care clinic, a dialysis clinic, or other third-party care providers. In some embodiments, the peritoneal dialysis machine and / or the hemodialysis machine can be a home machine, for example, treatment can be performed at the patient's home. As described above, the integrated care system can be applicable to other chronic diseases and can be connected to machines related to those diseases, including but not limited to chronic kidney disease, or one or more of the above-mentioned other chronic diseases and conditions. For example, machines 1200, 1300, 1400 can send patient data to the integrated care system 220, 220' for use in one or more algorithms as data for extraction and / or processing to determine whether ESRD patients are at risk of hospitalization.

[0121] refer to Fig.12 , a schematic diagram of an exemplary embodiment of a dialysis machine 1200 and a controller 1205 according to the present disclosure is shown. The dialysis machine 1200 may be a dialysis machine for performing dialysis treatment on a patient, for example, a peritoneal dialysis machine or a hemodialysis machine (see Figure 12-14 ). The controller 1205 can automatically control the performance of treatment functions during the course of the dialysis treatment. For example, the controller 1200 can control the dialysis treatment based on information received from the care analysis and guidance system 220, 220'. The controller 1205 can be operably connected to the sensor 1240 and deliver one or more signals to perform one or more treatment functions, or treatment processes associated with various treatment systems. Although Fig.12 The components are shown incorporated into the dialysis machine 1200, but at least one of the controller 1205, processor 1210, and memory 1220 may be configured to be externally and wired or wirelessly connected to the dialysis machine 1200 as a separate component of the dialysis system. In some embodiments, the controller 1205, processor 1210, and memory 1220 may be remote from the dialysis machine and configured to be capable of wireless communication.

[0122] In some embodiments, the controller 1205, processor 1210, and memory 1220 of the system or machine 1200, 1300, 1400 may receive signals indicative of one or more patient parameters from the sensor 1240. Communication between the controller 1205 and the treatment system may be bidirectional, whereby the treatment system acknowledges the control signal, and / or may provide status information associated with the treatment system and / or the requested operation. For example, the system status information may include a status associated with a particular operation to be performed by the treatment system (e.g., a trigger pump for delivering dialysate, a trigger pump and / or compressor for delivering filtered blood, etc.) and a status associated with a particular operation (e.g., ready to execute, executing, completed, successfully completed, queued for execution, waiting for a control signal, etc.).

[0123] The dialysis system or machine 1200, 1300, 1400 may also include at least one pump 1250 operatively connected to the controller 1205. The controller 1205 may also be operatively connected to one or more speakers 1230 and one or more microphones 1235 disposed in the system or dialysis machine 1200, 1300, 1400. The user input interface 1215 may include a combination of hardware and software components that allow the controller 1205 to communicate with an external entity such as a patient or other user. These components may be configured to be able to receive information from measures such as body movements or gestures and verbal intonations. In an embodiment, the components of the user input interface 1215 may provide information to an external entity. Examples of components that may be used within the user input interface 1215 include a keypad, a button, a microphone, a touch screen, a gesture recognition device, a display screen, and a speaker.

[0124] like Fig.12 As shown in , a sensor 1240 may be included for detecting and monitoring one or more parameters, and the sensor 1240 may be operably connected to at least the controller 1205, the processor 1210, and the memory 1220. The processor 1210 may be configured to be able to execute an operating system, and the operating system may provide platform services to the application software, for example, for operating the dialysis machine 1200. These platform services may include inter-process and network communications, file system management, and standard database operations. One or more of many operating systems may be used, and the examples are not limited to any particular operating system or operating system features. In some examples, the processor 1210 may be configured to be able to execute a real-time operating system (RTOS), such as RTLinux, or a non-real-time operating system, such as BSD or GNU / Linux. According to various examples, the processor 1210 may be a commercially available processor, such as a processor manufactured by INTEL, AMD, MOTOROLA, and FREESCALE. However, the processor 1210 may be any type of processor, multiprocessor, or controller, whether commercially available or specially manufactured. For example, according to one example, processor 1210 may include an MPC823 microprocessor manufactured by MOTOROLA.

[0125] Memory 1220 may include a computer-readable and writable non-volatile data storage medium configured to store non-transient instructions and data. In addition, memory 1220 may include a processor memory that stores data during operation of processor 1210. In some examples, processor memory includes a relatively high-performance, volatile, random access memory, such as a dynamic random access memory (DRAM), a static random access memory (SRAM), or a synchronous DRAM. However, processor memory may include any device for storing data, such as a non-volatile memory, that has sufficient information throughput and storage capacity to support the functions described herein. In addition, examples are not limited to a particular memory, memory system, or data storage system.

[0126] The instructions stored on the memory 1220 may include executable programs or other codes that can be executed by the processor 1210. The instructions may be persistently stored as coded signals, and the instructions may cause the processor 1210 to perform the functions described herein. The memory 1220 may include information recorded on or in a medium, and the information may be processed by the processor 1210 during the execution of the instructions. The memory 1220 may also include specifications for data logging for user timing requirements, timing for handling and / or operation, historical sensor information, and other databases, etc. The medium may be, for example, an optical disk, a magnetic disk, or a flash memory, etc., and may be permanently attached to or removed from the controller 1200.

[0127] Pressure sensors may be included for monitoring fluid pressure of the system or machine 1200, 1300, 1400, but the sensor 1240 may also include any of a heart rate sensor, a respiration sensor, a temperature sensor, a weight sensor, a video sensor, a thermal imaging sensor, an EEG sensor, a motion sensor, an audio sensor, an accelerometer, or a capacitive sensor. It should be understood that the sensor 1240 may include sensors with varying sampling rates, including wireless sensors. Based on the data monitored by the sensor 1240, patient parameters such as heart rate and respiration rate may be determined by the controller 1200.

[0128] The controller 1205 may be disposed in the machine 1200, 1300, 1400, or may be coupled to the machine 1200, 1300, 1400 via a communication port or wireless communication link schematically shown as a communication element 1206. For example, the communication element 1206 may connect the dialysis machine 1200, 1300, 1400 to the care analysis and guidance system 220, 220' or another remote system such as an external system or other clinical system. The dialysis machine 1200, 1300, 1400 may be connected to the integrated care system 220, 220' via the communication element 1206 so that the controller 1205 may send and receive information and other signals to the care analysis and guidance system 220, 220'. As described above, the care analysis and guidance system 220, 220' may direct the prescribed dialysis treatment directly to the dialysis machine based on information received from other systems (e.g., external systems, clinical systems) to ensure that the patient receives the correct treatment. The dialysis machine may also send data and other information to the care analysis and guidance system 220, 220' so that if the dialysis treatment needs to be adjusted, the care analysis and guidance system 220, 220' can ensure that any changes will not adversely affect the patient's health.

[0129] As a component disposed within the machine 1200, 1300, 1400, the controller 1205 may be operatively connected to any one or more of the sensor 1240, the pump 1250, the pump head 1404, 1406, etc. The controller 1205 may communicate control signals or trigger voltages to the system or components of the machine 1200, 1300, 1400. As discussed, an exemplary embodiment of the controller 1205 may include a wireless communication interface. The controller 1205 may detect remote devices to determine if any remote sensors may be used to augment any sensor data used to assess the patient.

[0130] Figures 13A-13B An example of a peritoneal dialysis (PD) system 1301 is shown, which is configured according to an exemplary embodiment of the system described herein. In some embodiments, the PD system 1301 can be a home PD system, for example, a PD system configured for use in a patient's home. The dialysis system 1301 can include a dialysis machine 1300 (e.g., a peritoneal dialysis machine 1300, also referred to as a PD cycler), and in some embodiments, the machine can sit on a cart 1304.

[0131] The dialysis machine 1302 may include a housing 1306, a door 1308, and a cassette interface including pump heads 1342, 1344 for contacting a disposable cassette or cassette 1315, wherein the cassette 1315 is located within a compartment (e.g., cavity 1305) formed between the cassette interface and the closed door 1308. The fluid line 1325 may be coupled to the cassette 1315 in a known manner, such as via a connector, and may also include a valve for controlling the flow of fluid into and out of a fluid bag containing fresh dialysate and warming fluid. In another embodiment, at least a portion of the fluid line 1325 may be integral with the cassette 1315. Prior to an operation, a user may open the door 1308 to insert a new cassette 1315, and remove a used cassette 1315 after an operation.

[0132] The cassette 1315 can be placed in the cavity 1305 of the machine 1300 for operation. During operation, dialysis fluid can flow into the patient's abdomen via the cassette 1315, and spent dialysate, waste, and / or excess fluid can be removed from the patient's abdomen via the cassette 1315. The door 1308 can be securely closed to the machine 1300. Peritoneal dialysis for a patient can include a total disposal of approximately 10 to 30 liters of fluid, wherein approximately 2 liters of dialysis fluid is pumped into the patient's abdomen, retained for a period of time, e.g., about an hour, and then pumped out of the patient's body. This process is repeated until the total disposal volume is reached, and typically occurs at night while the patient is asleep.

[0133] A heater tray 1316 can be positioned on top of the housing 1306. The heater tray 1316 can be of any size and shape to accommodate a bag of dialysate (e.g., a 5L dialysate bag) for batch heating. The dialysis machine 1300 can also include a user interface, such as a touch screen 1318 and a control panel 1320 that can be operated by a user (e.g., a caregiver or patient) to allow, for example, setting up, starting and / or terminating a dialysis treatment. In some embodiments, the heater tray 1316 can include a heating element 1335 for heating the dialysate before it is delivered to the patient.

[0134] The dialysate bag 1322 can be hung from a hook on the side of the cart 1334, and the heater bag 1324 can be positioned in the heater tray 1316. Hanging the dialysate bag 1322 can improve air management because the air contents can drain to the top portion of the dialysate bag 1322 by gravity. Fig. 13B1, but any number "n" of dialysate bags may be connected to the dialysis machine 1300 (e.g., 1 to 5 bags, or more), and the reference to the first and second bags does not limit the total number of bags used in the dialysis system 1301. For example, the dialysis machine may have dialysate bags 1322a, ..., 1322n that may be connected in the system 1301. In some embodiments, connectors and tube ports may connect the dialysate bags 1322 and lines for transferring dialysate. The dialysate from the dialysate bag 1322 may be transferred to the heating bag 1324 in batches. For example, a batch of dialysate may be transferred from the dialysate bag 1322 to the heater bag 1324, where the dialysate is heated by the heating element 1340. When the batch of dialysate has reached a predetermined temperature (e.g., approximately 98°-100°F, 37°C), the batch of dialysate may flow into the patient. The dialysate bag 1322 and the heater bag 1324 may be connected to the cassette 1315 via a dialysate bag line or tube 1325 and a heater bag line or tube 1328, respectively. The dialysate bag line 1325 may be used to transfer dialysate from the dialysate bag 1322 to the cassette during use, and the heater bag line 1328 may be used to transfer dialysate back and forth between the cassette and the heater bag 1324 during use. In addition, a patient line 1336 and a drain line 1332 may be connected to the cassette 1315. The patient line 1336 may be connected to the abdomen of the patient via a catheter, and may be used to transfer dialysate back and forth between the cassette and the peritoneal cavity of the patient through the pump heads 1342, 1344 during use. The drain line 1332 may be connected to a drain or drain container, and may be used to transfer dialysate from the cassette to the drain or drain container during use.

[0135] Although in some embodiments, the dialysate can be heated in batches as described above, in other embodiments, the dialysis machine can heat the dialysate by in-line heating, for example, continuously flowing the dialysate through a warmer bag located between heating elements before the dialysate is delivered to the patient. For example, instead of placing a heater bag for batch heating on a heater tray, one or more heating elements can be provided inside the dialysis machine. The warmer bag can be inserted into the dialysis machine via an opening. It should also be understood that the warmer bag can be connected to the dialysis machine via a tube (e.g., tube 1325) or a fluid line via a box. The tube can be connectable so that the dialysate can flow from the dialysate bag through the warmer bag for heating and flow to the patient.

[0136] In such an in-line heating embodiment, the warmer bag can be configured so that the dialysate can flow continuously through the warmer bag (rather than being transferred in batches for batch heating) to reach a predetermined temperature before flowing into the patient. For example, in some embodiments, the dialysate can flow continuously through the warmer bag at a rate of between about 100-300 mL / min. An internal heating element (not shown) can be located above and / or below the opening so that when the warmer bag is inserted into the opening, one or more heating elements can affect the temperature of the dialysate flowing through the warmer bag. In some embodiments, the internal warmer bag can alternatively be a portion of a tube in the system that is passed through, surrounded by, or otherwise configured relative to the heating element.

[0137] The touch screen 1318 and control panel 1320 may allow an operator to input various treatment parameters to the dialysis machine 1300, as well as to otherwise control the dialysis machine 1300. In addition, the touch screen 1318 may function as a display. The touch screen 1318 may function to provide information to the patient and the operator of the dialysis system 1301. For example, the touch screen 1318 may display information related to the dialysis treatment to be applied to the patient, including information related to the prescription.

[0138] The dialysis machine 1300 may include a processing module 1302 inside the dialysis machine 1300, the processing module 1302 being configured to be in communication with a touch screen 1318 and a control panel 1320. The processing module 1302 may be configured to receive data from the touch screen 1318, the control panel 1320, and sensors, such as weight, air, flow, temperature, and / or pressure sensors, and control the dialysis machine 1300 based on the received data. For example, the processing module 1302 may adjust operating parameters of the dialysis machine 1300.

[0139] The dialysis machine 1300 may be configured to be connected to a network 1303. The connection to the network 1303 may be via a wired and / or wireless connection. The dialysis machine 1300 may include a connection component 1304 configured to facilitate connection to the network 1303. The connection component 1304 may be a transceiver for wireless connection and / or other signal processor for processing signals sent and received via a wired connection. Other medical devices (e.g., other dialysis machines) or components may be configured to be connected to the network 1303 and communicate with the dialysis machine 1300.

[0140] The user interface portion, such as the touch screen 1318 and / or the display 1320, may include one or more buttons for selecting and / or inputting user information. The touch screen 1318 and / or the display 1320 may be operatively connected to a controller (not shown) and disposed in the machine 1300 for receiving and processing input for operating the dialysis machine 1300.

[0141] In some embodiments, the machine 1200, 1300, 1400 may - alternatively or simultaneously or in conjunction with sending information to the integrated care system 220, 220' - wirelessly transmit (e.g., via a wireless Internet connection) information or alerts to a remote location, including but not limited to a doctor's office, hospital, call center, and technical support. For example, the machine 1200, 1300, 1400 may provide real-time remote monitoring of machine operation and patient parameters. The memory 1220 of the machine 1200 may store data, or the machine 1200, 1300, 1400 may transmit data to a local or remote server at predetermined intervals.

[0142] Fig.14 A schematic diagram of an exemplary embodiment of a dialysis system 1400 according to the present disclosure is illustrated. The dialysis system 1400 can be configured to provide hemodialysis treatment to a patient 1401. A fluid reservoir 1402 can deliver fresh dialysate to a dialyzer 1404 via a tube 1403, and once the dialysate passes through the dialyzer 1404, a reservoir 1406 can receive the used dialysate via a tube 1405. The hemodialysis operation can filter particles and / or contaminants from the patient's blood through a patient-external filtration device, such as a dialyzer 1404. Since the dialysate passes through the dialyzer 1404, unfiltered patient blood also enters the dialyzer via a tube 1407, and the filtered blood is returned to the patient via a tube 1409. Arterial pressure can be monitored via a pressure sensor 1410, inflow pressure can be monitored via a sensor 1418, and venous pressure can be monitored via a pressure sensor 1414. Air traps and detectors 1416 can ensure that air is not introduced into the patient's blood as it is filtered and returned to the patient 1401. The flow of blood and the flow of dialysate are controlled via respective pumps, including a blood pump 1412 and a fluid pump 1420. Heparin 1422 (a blood thinner) can be used in conjunction with saline 1424 to ensure that blood clots do not form or block blood flow through the system.

[0143] In some embodiments, the dialysis system 1400 may include a controller 1450, which may be similar to the controller 1450 described above for the dialysis machines 1400, 1400. The controller 1450 may be configured to monitor fluid pressure readings to identify fluctuations in patient parameters such as heart rate and / or respiratory rate. In some embodiments, the patient's heart rate and / or respiratory rate may be determined by the fluid pressure in the fluid flow line and the fluid bag. The controller 1450 may also be operably connected to another sensor or sensor system and / or communicate with another sensor or sensor system, although the controller 1450 may use any available data about the patient's biological function or other patient parameters. For example, the controller 1450 may send patient data to the integrated care system 220, 220' for use in one or more algorithms as data for extraction and processing in order to determine whether an ESRD patient is at risk of hospitalization.

[0144] Fig.15 One embodiment of an exemplary computing architecture 1500 suitable for implementing various embodiments as previously described is shown. In various embodiments, the computing architecture 1500 may include or be implemented as part of an electronic device. In some embodiments, the computing architecture 1500 may represent, for example, a computing device 410 and / or a platform 505 and / or a component of an integrated care system 220, 220'. The embodiments are not limited in this context.

[0145] As used in this application, the terms "system" and "component" and "module" mean an entity related to a computer, either hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by the exemplary computing architecture 1500. For example, a component can be, but is not limited to, a process running on a processor, a processor, a hard drive, multiple storage drives (optical and / or magnetic storage media), an object, an executable file, an execution thread, a program, and / or a computer. As an illustration, both an application running on a server and a server can be a component. One or more components can be within a process and / or an execution thread, and a component can be located on a computer and / or distributed between two or more computers. In addition, components can be communicatively coupled to each other through various types of communication media to coordinate operations. Coordination may involve unidirectional or bidirectional information exchange. For example, a component can communicate information in the form of a signal transmitted on a communication medium. The information can be implemented as a signal assigned to various signal lines. In such an assignment, each message is a signal. However, other embodiments may alternatively use data messages. Such data messages can be sent through various connections. Exemplary connections include parallel interfaces, serial interfaces, and bus interfaces.

[0146] The computing architecture 1500 includes various common computing elements such as one or more processors, multi-core processors, coprocessors, memory units, chipsets, controllers, peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input / output (I / O) components, power supplies, etc. However, the embodiments are not limited to being implemented by the computing architecture 1500.

[0147] like Fig.15 As shown, computing architecture 1500 includes processing unit 1504, system memory 1506, and system bus 1508. Processing unit 1504 can be any of a variety of commercially available processors, including but not limited to Intel and Intel processors; application, embedded and security processors; Intel and Intel processors; IBM and Cell processors; Core (2) and Intel processors; and similar processors. Dual microprocessors, multi-core processors, and other multi-processor architectures can also be used as processing unit 1504.

[0148] The system bus 1508 provides an interface to the processing unit 1504 for system components including, but not limited to, the system memory 1506. The system bus 1508 may be any of a variety of types of bus structures that may further interconnect to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. Interface adapters may be connected to the system bus 1508 via a slot architecture. Example slot architectures may include, but are not limited to, Accelerated Graphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, Personal Computer Memory Card International Association (PCMCIA), and the like.

[0149] The system memory 1506 may include various types of computer-readable storage media in the form of one or more higher speed memory cells, such as read-only memory (ROM), random access memory (RAM), dynamic RAM (DRAM), double data rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory such as ferroelectric polymer memory, austenite memory, phase change or ferroelectric memory, silicon oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical cards, arrays of devices such as redundant array of independent disks (RAID) drives, solid-state memory devices (e.g., USB memory, solid-state drive (SSD), and any other type of storage medium suitable for storing information. Fig.15In the illustrative embodiment shown in FIG. 1 , system memory 1506 may include nonvolatile memory 1510 and / or volatile memory 1512. A basic input / output system (BIOS) may be stored in nonvolatile memory 1510.

[0150] The computer 1502 may include various types of computer-readable storage media in the form of one or more lower-speed memory units, including an internal (or external) hard disk drive (HDD) 1514, a magnetic floppy disk drive (FDD) 1516 that reads from or writes to a removable disk 1518, and an optical drive 1520 that reads from or writes to a removable disk 1522 (e.g., a CD-ROM or DVD). The HDD 1514, FDD 1516, and optical drive 1520 may be connected to the system bus 1508 via a HDD interface 1524, a FDD interface 1526, and an optical drive interface 1528, respectively. The HDD interface 1524 for external drive implementations may include at least one or both of a Universal Serial Bus (USB) and IEEE 884 interface technologies.

[0151] The drives and associated computer-readable media provide volatile and / or nonvolatile storage of data, data structures, computer-executable instructions, etc. For example, a number of program modules may be stored in the drives and memory units 1510, 1512, including an operating system 1530, one or more application programs 1532, other program modules 1534, and program data 1536. In one embodiment, the one or more application programs 1532, other program modules 1534, and program data 1536 may include, for example, various applications and / or components of the systems and / or devices 200, 200', 220, 220', 400, 500.

[0152] A user may enter commands and information into the computer 1502 through one or more wired / wireless input devices, such as a keyboard 1528 and a pointing device such as a mouse 1540. Other input devices may include a microphone, an infrared (IR) remote control, a radio frequency (RF) remote control, a game pad, a stylus, a card reader, a dongle, a fingerprint reader, a glove, a graphics tablet, a joystick, a keyboard, a retina reader, a touch screen (e.g., capacitive, resistive, etc.), a trackball, a trackpad, a sensor, a stylus, etc. These and other input devices are typically connected to the processing unit 1504 through an input device interface 1542 coupled to the system bus 1508, but may be connected through other interfaces such as a parallel port, an IEEE894 serial port, a game port, a USB port, an IR port, etc.

[0153] A monitor 1544 or other type of display device is also connected to the system bus 1508 via an interface, such as a video adapter 1546. The monitor 1544 may be internal or external to the computer 802. In addition to the monitor 1544, computers typically include other peripheral output devices such as speakers, printers, and the like.

[0154] The computer 1502 can operate in a network environment using logical connections via wired and / or wireless communications to one or more remote computers, such as remote computer 1548. The remote computer 1548 can be a workstation, server computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer device or other public network node, and typically includes many or all of the elements described relative to the computer 1502, but only a memory / storage device 1550 is shown for simplicity. The depicted logical connections include wired / wireless connections to a local area network (LAN) 1552 and / or a larger network, such as a wide area network (WAN) 1554. Such LAN and WAN networking environments are common in offices and companies, and facilitate enterprise-wide computer networks, such as intranets, all of which can be connected to a global communications network, such as the Internet.

[0155] When used in a LAN networking environment, the computer 1502 is connected to the LAN 1552 through a wired and / or wireless communication network interface or adapter 1556. The adapter 1556 can facilitate wired and / or wireless communication to the LAN 1552, which can also include a wireless access point disposed thereon for communicating with the wireless functionality of the adapter 1556.

[0156] When used in a WAN networking environment, the computer 1502 may include a modem 1558, or be connected to a communications server on the WAN 1554, or have other devices for establishing communications over the WAN 1554, such as over the Internet. The modem 1558, which may be internal or external and may be a wired and / or wireless device, is connected to the system bus 1508 via the input device interface 1542. In a networked environment, program modules depicted relative to the computer 1502, or portions thereof, may be stored in the remote memory / storage device 1550. It should be appreciated that the network connections shown are exemplary and other methods of establishing a communications link between the computers may be used.

[0157] The computer 1502 is operable to communicate with wired and wireless devices or entities using the IEEE 802 family of standards, such as wireless devices operatively arranged in wireless communications (e.g., IEEE 802.16 over-the-air modulation techniques). This includes at least Wi-Fi (or Wireless Fidelity), WiMax, and Bluetooth. TM Wireless technology, etc. Therefore, the communication can be a predefined structure like traditional networks, or just a simple ad hoc communication between at least two devices. Wi-Fi networks use radio technologies called IEEE802.11x (a, b, g, n, etc.) to provide secure, reliable, and fast wireless connections. Wi-Fi networks can be used to connect computers to each other, to the Internet, and to wired networks (which use media and functions related to IEEE802.3).

[0158] Some embodiments of the disclosed system may be implemented, for example, using a storage medium, a computer-readable medium, or an article of manufacture, which may store instructions or instruction sets that, if executed by a machine (i.e., a processor or microcontroller), may cause the machine to perform methods and / or operations according to embodiments of the present disclosure. In addition, a server or database server may include a machine-readable medium configured to store machine-executable program instructions. Such a machine may include, for example, any suitable processing platform, computing platform, computing device, processing device, computing system, processing system, computer, processor, etc., and may be implemented using any suitable combination of hardware, software, firmware, or a combination thereof, and may be used for a system, subsystem, component, or subcomponent. The computer-readable medium or article may include, for example, any suitable type of memory unit, memory device, memory article, memory medium, storage device, storage article, storage medium and / or storage unit, such as memory (including non-transitory memory), removable or non-removable media, erasable or non-erasable media, writable or rewritable media, digital or analog media, hard disk, floppy disk, compact disk read-only memory (CD-ROM), compact disk recordable (CD-R), compact disk rewritable (CD-RW), optical disk, magnetic media, magneto-optical media, removable memory cards or disks, various types of digital versatile disks (DVDs), magnetic tapes, cassettes, etc. The instructions may include any suitable type of code implemented using any suitable high-level, low-level, object-oriented, visual, compiled and / or interpreted programming language, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, encrypted code, etc.

[0159] Many specific details have been set forth herein to provide a thorough understanding of the embodiments. However, those skilled in the art will appreciate that the embodiments may be practiced without these specific details. In other cases, well-known operations, components, and circuits are not described in detail to avoid confusing the embodiments. It is understood that the specific structural and functional details disclosed herein may be representative and do not necessarily limit the scope of the embodiments.

[0160] Some embodiments may be described using the expressions "coupled" and "connected" and their derivatives. These terms are not intended to be synonymous with each other. For example, some embodiments may be described using the terms "connected" and / or "coupled" to indicate that two or more elements are in direct physical or electrical contact with each other. However, the term "coupled" may also mean that two or more elements are not in direct contact with each other, but still cooperate or interact with each other.

[0161] Unless expressly stated otherwise, it is understood that terms such as "processing", "computing", "calculating", "determining", etc. refer to measures and / or processes of a computer or computing system or similar electronic computing device that manipulate and / or transform data represented as physical quantities (e.g., electronic) in registers and / or memories of the computing system into other data similarly represented as physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the computing system. The embodiments are not limited in this context.

[0162] It should be noted that the methods described herein do not have to be executed in the order described or in any particular order. In addition, various activities described with respect to the methods identified herein can be executed in serial or parallel manner.

[0163] Although specific embodiments have been shown and described herein, it should be understood that any arrangement calculated to achieve the same purpose may replace the specific embodiments shown. The present disclosure is intended to cover any and all modifications or variations of the various embodiments. It should be understood that the above description is made in an illustrative manner, rather than restrictive. In reviewing the above description, the combination of the above embodiments and other embodiments not specifically described herein will be apparent to those skilled in the art. Therefore, the scope of the various embodiments includes any other application using the above compositions, structures and methods.

[0164] Although the subject matter has been described in language specific to structural features and / or methodological measures, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or measures described above. Rather, the specific features and measures described above are disclosed as example forms of implementing the claims.

[0165] As used herein, an element or operation described in the singular and prefixed with the word "one" or "an" should be understood to not exclude plural elements or operations, unless such exclusion is explicitly described. In addition, reference to "one embodiment" of the present disclosure is not intended to be interpreted as excluding the existence of other embodiments that also incorporate the described features.

[0166] To the extent used in this specification and in the claims, recitations in the general form of "at least one of [a] and [b]" should be interpreted as disjunctive. For example, recitations of "at least one of [a], [b], and [c]" would include [a] alone, [b] alone, [c] alone, or any combination of [a], [b], and [c].

[0167] The present disclosure is not limited in scope by the specific embodiments described herein. In fact, in addition to those embodiments described herein, various other embodiments and modifications of the present disclosure will be apparent to those of ordinary skill in the art based on the foregoing description and accompanying drawings. Therefore, such other embodiments and modifications are intended to fall within the scope of the present disclosure. In addition, although the present disclosure has been described herein in the context of a specific implementation in a specific environment for a specific purpose, those of ordinary skill in the art will recognize that its practicality is not limited thereto, and the present disclosure can be advantageously implemented in any number of environments for any number of purposes.

Claims

1. A system for determining the risk of hospitalization for a patient with end-stage renal disease (ESRD), the system comprising: An integrated care system that is configured to: extracting patient data from one or more databases corresponding to a pool of patients with end-stage renal disease (ESRD); sending information to and receiving information from a dialysis unit or dialysis machine; generating, using a predictive model utilizing the extracted patient data, for each of the patients in the pool of patients a corresponding expected probability of hospitalization within a predetermined time period; identifying a subset of the pool of patients having a higher corresponding expected probability of hospitalization than other patients in the pool of patients; determining, for each patient in the subset of the pool of patients, at least one significant factor from the patient data that increases an expected probability of hospitalization; and Generate a report that ranks the pool of patients according to their respective expected probabilities of hospitalization Provide at least one significant factor for each corresponding patient, and At least one clinical intervention is provided for each patient in the subset of the pool of patients, the at least one clinical intervention selected to target the at least one significant factor to reduce the expected probability of hospitalization for the at least one patient.

2. The system according to claim 1, wherein: The predictive model includes a gradient boosting framework.

3. The system according to claim 1, wherein: The integrated care system is configured to identify the at least one significant factor using Shapley's Add-On Interpretation for each patient.

4. The system according to claim 1, wherein: The predetermined period of time is 7 days or less.

5. The system according to claim 1, wherein: The extracted patient data includes patient demographic data, patient laboratory values, patient disposition data, or a comprehensive evaluation of the patient, or a combination thereof.

6. The system according to claim 5, wherein: The patient's demographic data includes the patient's date of birth, the patient's date of first dialysis, the patient's gender, the patient's race, the patient's ethnicity, or the patient's marital status, or a combination thereof.

7. The system according to claim 5, wherein: The patient's laboratory value includes the patient's hemoglobin level, or the patient's albumin level, or a combination thereof.

8. The system according to claim 5, wherein: The patient's laboratory values ​​are provided as an average value, a maximum value, a minimum value, a value spike, a value drop, or a trend value, or a combination thereof, over a specified time period.

9. The system according to claim 5, wherein: The patient's treatment data includes vital signs of the patient, and wherein the vital signs of the patient are provided as an average value, a maximum value, a minimum value, a value spike, a value drop, or a trend value, or a combination thereof, within a specified time period.

10. The system according to claim 5, wherein: The patient's comprehensive evaluation may include the patient's recent hospitalization history, the patient's history of missed appointments, any patient notes or complaints, evaluations by nurses or other medical professionals, or any delivered medications, or a combination thereof.

11. The system according to claim 1, wherein: The predictive model is constructed based on historical data from other patients.

12. A computer program product comprising computer executable instructions, which when executed by a computer cause the computer to perform the following method, comprising: extracting patient data from one or more databases corresponding to a pool of patients with end-stage renal disease (ESRD); sending information to and receiving information from a dialysis unit or dialysis machine; using a predictive model utilizing the extracted patient data to generate, for each patient in the pool of patients, a corresponding expected probability of hospitalization within a predetermined time period; identifying a subset of the pool of patients having a higher corresponding expected probability of hospitalization than other patients in the pool of patients; determining, for each patient in the subset of the pool of patients, at least one significant factor from the patient data that increases an expected probability of hospitalization; and Determining at least one clinical intervention for each patient in the subset of the pool of patients, the at least one clinical intervention selected to target the at least one significant factor to reduce the expected probability of hospitalization for the at least one patient, wherein the at least one clinical intervention comprises at least one of: (a) administering one or more dialysis treatments in addition to the patient's existing dialysis schedule, (b) extending the duration of the patient's dialysis treatments, (c) adjusting the patient's target weight for a dialysis treatment, (d) adjusting the dialysate sodium concentration for the patient's dialysis treatment, and (e) adjusting the patient's blood pressure medication.

13. The computer program product of claim 12, wherein: The predictive model includes a gradient boosting framework.

14. The computer program product of claim 12, wherein: The at least one significant factor was identified for each patient using Shapley Add-On Interpretation.

15. The computer program product of claim 12, wherein: The predetermined period of time is 7 days or less.

16. The computer program product of claim 12, wherein: The extracted patient data includes patient demographic data, patient laboratory values, patient disposition data, or a comprehensive evaluation of the patient, or a combination thereof.

17. The computer program product of claim 16, wherein: The patient's demographic data includes the patient's date of birth, the patient's date of first dialysis, the patient's gender, the patient's race, the patient's ethnicity, or the patient's marital status, or a combination thereof.

18. The computer program product of claim 16, wherein: The patient's laboratory value includes the patient's hemoglobin level, or the patient's albumin level, or a combination thereof.

19. The computer program product of claim 16, wherein: The patient's laboratory values ​​are provided as an average value, a maximum value, a minimum value, a value spike, a value drop, or a trend value, or a combination thereof, over a specified time period.

20. The computer program product of claim 16, wherein: The patient's treatment data includes vital signs of the patient, and wherein the vital signs of the patient are provided as an average value, a maximum value, a minimum value, a value spike, a value drop, or a trend value, or a combination thereof, within a specified time period.

21. The computer program product of claim 16, wherein: The patient's comprehensive evaluation may include the patient's recent hospitalization history, the patient's history of missed appointments, any patient notes or complaints, evaluations by nurses or other medical professionals, or any delivered medications, or a combination thereof.

22. The computer program product of claim 12, wherein: The predictive model is constructed based on historical data from other patients.

23. The computer program product of claim 12, further comprising generating a report that ranks the pool of patients according to their respective expected probabilities of hospitalization, wherein: The report provides the at least one significant factor for each respective patient.

24. The computer program product of claim 23, further comprising providing the generated report to one or more health care providers.

25. The computer program product of claim 12, further comprising transmitting an automated alert to one or more healthcare providers based on the expected probability of hospitalization.

26. The computer program product of claim 12, wherein: The pool of patients were patients of the ESRD Seamless Care Organization (ESCO).

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