Patent Application
20170357756
As the cost of providing health care continues to increase at an unsustainable rate, health care providers (especially physicians) are increasingly being held responsible for controlling cost in an effort to provide high quality care while controlling costs. Drivers of this shift in responsibility include the federal government (Medicare, Medicaid, Va., CHiPs), state governments, third party payers (both for-profit and not-for-profit), and Accountable Care Organizations (ACOs) as well as individual hospitals and medical groups. Increasingly, health care providers are being asked to share in the financial risk in providing medical care.
A method for determining and indicating values of medical treatment plans includes a processor creating value baselines comprising health metric values for approved plans of care; receiving a request from a client device based on the client device detecting an activity indicating a patient-related event, the request identifying the patient-related event; generating a health value continuum based on the patient-related event; generating a comparison of the health value continuum to a value baseline; and providing data and instructions to the client device to display on a display page, a representation of the health value continuum to value baseline comparison.
A processor-implemented method for determining and indicating values of medical treatment plans includes a processor creating value baselines comprising health metric values for approved plans of care; receiving a request from a client device based on the client device detecting an activity indicating a patient-related event, the request identifying a visit associated with a patient generating a health value continuum based on the visit; generating a comparison of the health value continuum to a value baseline; and providing data and instructions to display on a display page, a representation of the health value continuum to value baseline comparison.
A method for determining and indicating values of medical treatment plans, the method executed over a client-server architecture, including a server creating value baselines comprising health metric values for approved plans of care; a client detecting activity related to medical care for a patient; the client sending and the server receiving a request from the client device identifying a patient visit that has an associated diagnosis; and the server: determining the activity warrants generating a health value continuum, generating a health value continuum corresponding to the diagnosis, generating a comparison of the health value continuum to the value baseline, and providing data and instructions to the client to display a representation of the health value continuum to value baseline comparison.
A method executed by a processor of a health value analytics system in communication with a device external to the health value analytics system, includes the processor receiving an indication of a patient-related event from the external device, the patient-related event referencing a visit of a patient; and based on the visit reference, the processor: determining a need to generate a health value continuum: directing generation of the health value continuum, directing generation of a comparison of the health value continuum to a value baseline for an approved plan of care, and directing the provision of data and instructions to display on a display page, a representation of the health value continuum to value baseline comparison.
A method for determining and indicating values of medical treatment plans, includes a server, in communication with a client: receiving from the client a communication defining a patient-related event; the server, in response to the communication: determining a need to generate a value continuum, generating the value continuum, generating a comparison of the value continuum to a value baselines comprising health metric values of a designed plan of care, and providing a representation of the comparison, and instructions, to the client to display the representation of the comparison.
The detailed description refers to the following drawings, in which like numerals refer to like objects, and in which:
Large medical facilities (e.g., hospitals) may employ large, secure, and carefully regulated and monitored electronic medical record systems (EMR) (sometimes known as electronic health records (EHR) systems), and the EMR systems may use a dedicated EMR server to access a large EMR database that contains the electronic medical records. End users (for example, physicians, nurses, other health care providers, and other hospital staff) may interact with the EMR database using, for example, laptop and desktop computers, work stations, notepads, and smartphones. In some situations, end users require rapid, real-time access to the EMR database. At all times, end users require accurate and up-to-date information from the EMR system. The resulting high demand for information, conveyed in the form of requests from end user devices, and supplied in the form of responses from the EMR system, may overload the EMR system and result in slower than desired information retrieval.
For example, health care providers may lack information regarding the costs of services provided within a hospital or medical center. While health care providers (e.g., physicians) often are cognizant of their office charges and perhaps even their daily visit charges in a hospital setting, they typically do not know the hospital's costs associated with providing service to their patients. In addition, the providers usually do not know the average historical cost to treat a particular condition or the expected overall reimbursement that a health care facility may receive for patients being treated at the facility.
On the other hand, hospitals and other health care facilities may use nationally accepted formulas for each hospitalization of a patient to arrive at an expected payment/reimbursement. Additionally, hospitals generally maintain a comprehensive charge list of the costs of materials and time for each component of care delivered. Physicians and other health care providers typically lack access to these two hospital-based components of accounting, yet these components are major drivers of the cost and value of health care delivered.
Currently, there is no mechanism for combining the available accounting information from discrete information sources for all types of care, processing this information, and then presenting the information to a provider in real-time, on-demand, in a way that helps the health care provider determine an appropriate plan of care. Current methods of reporting are incomplete, inaccurate, delayed (i.e., not real-time), and/or cumbersome (e.g., information not presented in a useful, easily readable manner).
It is therefore desirable for a provider to be able to see where the cost of care of a patient falls on a cost of care continuum, from the time of diagnosis to completion of all care delivered (e.g., a final physical therapy session six months after initial medical contact). The determination of “value” has become the new mandate from businesses, payers, and the patients themselves, each of whom look to reduce health care costs. The market is ready for a system that can determine and monitor the value of health care being delivered in multiple settings from the point of diagnosis through the last service provided, whether inpatient or outpatient.
To address these issues, embodiments of this disclosure provide systems and methods for determining and indicating value of health care. The disclosed systems and methods provide and process health care cost and value information on a regular, ongoing basis, and/or on an episodic or ad hoc basis, and may automatically update the information when changes are needed or desired. A health care provider may see where the value of the patient's health care falls within a value continuum after or as a result of every input.
The disclosed systems help health care providers monitor, manage, and maximize value in the delivery of care. In some embodiments, the disclosed systems are capable of determining the average cost to treat a patient diagnosis. The systems receive information relating to a plurality of health care services associated with a patient. The systems have the ability to associate a cost with each of the health care services and the ability to aggregate the costs for the health care services. In addition, the disclosed systems are capable of presenting the service cost and value data to the health care provider in a way that it may be used to determine an appropriate plan of care for the patient.
Multiple end user devices 104-110 communicate via the network 102. The user devices 104-110 generally denote devices used by health care providers or their assistants to access, provide, update, or remove information associated with patient electronic medical records (EMRs), health care costs, and health care value measurements. The user devices 104-110 include fixed or mobile devices that may communicate over wired, wireless, or other connections with at least one of the networks 102. In this example, the user devices 104-110 include a personal digital assistant 104, a smartphone 106, a tablet computer 108, and a desktop or laptop computer 110. Any other or additional user devices may be used in the system 100, and the system 100 may support interaction with any number of user devices.
One or more servers 112 also may communicate over the network 102. Each server 112 may represent a computing device that processes information associated with patient EMRs, health care costs, and value measurements, as described in greater detail below. Information associated with the operations of the server 112 is stored in one or more related databases 114. For example, each server 112 retrieves and provides information about one or more patient health care records, one or more medical or health care procedures associated with the patient, and cost or reimbursement information associated with the medical or health care procedures. Different information or additional information also may be provided by each server 112. Each server 112 includes any suitable structure for providing information and interacting with user devices. The database 114 includes any suitable structure for storing information and for facilitating retrieval of information (e.g., a relational database accessible through Structured Query Language (SQL) commands).
One or more operator stations 116 may interact with the server 112. For example, an operator station 116 allows health care personnel to access, provide, update, or remove information associated with patient EMRs, health care costs, and health care value measurements. Each operator station 116 includes any suitable structure supporting interaction with a server, such as a desktop computer, laptop computer, thin client, or mobile device.
As described herein, each user device 104-110 may execute an application or may access an application executed by the server 112. The application allows a user to interact with, receive information from, and provide information to, the server 112. For example, the server 112 may receive requests from the user devices 104-110 and in response to receiving requests from the user devices 104-110 provides information from the database 114. Other operations supported by the application are described herein.
Although
The processing device 204 processes software/firmware instructions, such as instructions loaded from the storage 208 into the memory 206. The processing device 204 may include a single processor, multiple processors, one or more multi-processor cores, or other type(s) of processor(s) depending on the particular implementation. As an example, the processing device 204 is implemented using a number of heterogeneous processor systems in which a main processor is present with secondary processors on a single chip. As another example, the processing device 204 is a symmetric multi-processor system containing multiple processors of a same or similar type. Any suitable processing device(s) may be used.
The memory 206 and the storage 208 are examples of storage devices that may be used in the device 200. Such a storage device may be any piece of hardware capable of storing information, such as data, program code, or other suitable information on a temporary or permanent basis. The memory 206 may be a random access memory or other volatile or non-volatile storage device(s). The storage 208 contains one or more components or devices, such as a hard drive, flash memory, optical disc, or other non-transitory computer-readable storage device(s). A storage device may be fixed or removable, such as when a removable hard drive or USB thumb drive is used.
The communications unit 210 provides for communications with other systems or devices. For example, the communications unit 210 includes a network interface card or a wireless transceiver. The communications unit 210 provides communications through physical or wireless communications links.
The I/O unit 212 allows for input and output of data using other components connected to or integrated within the device 200. For example, the I/O unit 212 provides a connection for user input through a keyboard, a mouse, a microphone, or another input device. The I/O unit 212 also sends output to a display, printer, speaker, or other output device. The I/O unit 212 alternatively includes a keyboard, a mouse, a speaker, a microphone, or another input or output device(s). If the device 200 includes a display 214, the display or display interface 214 provides a mechanism to visually present information to a user. In some user devices, the display is represented as a touchscreen.
Program code for an operating system, applications, or other programs is located in the storage devices 216, which are in communication with the processing device 204 through the bus system 202. Instructions forming the programs are loaded into the memory 206 for processing by the processing device 204.
Returning to
The information may be used individually (e.g., for real-time individual decision making by a health care provider) and for comparisons between providers and provider groups (e.g., using historical reporting features). For example, for an expensive procedure (e.g., a hip replacement), one provide group might include members who charge lower rates, but who use more expensive devices. This provider group may be compared against another provider group whose members charge higher rates, but who use less expensive devices. The information may be used to compare individual components of care (e.g., surgeon costs, device costs, and the like) and overall cost (e.g., the total cost for the hip replacement).
Additional details of the system 100 may be more readily understood by way of an example. For this example, consider a child who is admitted to a hospital for pneumonia. Before admission to the hospital, a health care provider (e.g., a physician) will have performed an examination and a work up of the patient (e.g., in the doctor's office, at an emergency care facility, or at another suitable location). Based on the examination, the physician has determined that hospitalization is needed for the patient. The physician writes admission orders to admit the patient to the hospital with a diagnosis of pneumonia. In addition to the pneumonia diagnosis, there may be co-morbidities. For example, the patient may have a supplemental oxygen requirement. Due to vomiting, the patient may be dehydrated and have low potassium. Thus, the primary diagnosis for the patient is acute pneumonia; secondary diagnoses are hypoxemia, dehydration, and hypokalemia.
Once a patient is admitted to a hospital or other health care facility, a clinical documentation improvement (CDI) specialist reviews the admitting physician's diagnosis, and the patient's medical history and current physical, enters the diagnoses in International Classification of Diseases (ICD) codes such as in ICD code groups ICD-9 or ICD-10, and executes a DRG grouper application to aggregate the selected ICD-9 or ICD-10 codes to produce an initial DRG code, known as a working DRG.
Estimated reimbursement information may be obtained from the working DRG. For example, the working DRG (the diagnoses determined from the medical record) may be multiplied by the relative weight of the DRG (a multiplier determined by the Centers for Medicare & Medicaid Services (CMS) that scores the severity of the DRG) and also multiplied by a “blended rate” (a CMS-determined multiplier that accounts for local cost influences including wage index of employees, percentage of indigent care provided, target populations, local salary and cost report information) to arrive at the expected reimbursement for that visit. The hospital also may maintain a “charge description master,” which is a list of all the hospital's charges and costs.
In addition to (or in lieu of) expected reimbursement information, the diagnosis (e.g., from ICD-9 or ICD-10 codes), the working DRG, or other suitable diagnosis information may also be used to obtain expected cost information. For example, an “average cost to treat” may be obtained based on a working DRG. A baseline “average cost to treat” may be determined in advance for each DRG. These baseline “average cost to treat” values may be determined empirically by examining average total costs of treatment over time at a particular facility or group of facilities, for a particular physician group, and the like. For example, an average cost to treat for an appendectomy might be determined by examining a total cost of treatment for all appendectomies at a hospital over a two-year period. In some embodiments, the average cost to treat may be determined directly from the ICD9 or ICD10 codes or other diagnosis information. In some embodiments, the average cost to treat may be determined using a neural network that includes multiple inputs, such as age, gender, ICD code(s), DRG(s), time of day, and the like.
In some embodiments, the average cost to treat may be determined based on a designed plan of care. For a particular physician group, and for a particular diagnosis, the designed plan of care may represent an authorized or approved plan of care. The designed plan of care may include components such as orders, procedures, medications, for example. The designed plan of care then may constitute, or may be used to establish, a cost to treat baseline against which the aggregated costs are compared, as described herein. The designed plan of care may be determined by a group of experts using evidence-based medicine or clinical best practices. For example, the designed plan of care may be determined by a governmental or regulatory agency, by a corporate in-house physician group, or by any other suitable organization or group. Such designed plans of care already have been developed, reviewed, and approved for strokes, pneumonia, heart attacks, chest pain, and other common medical issues, as known in the art. The designed plan of care may include an order set that also includes target times to perform each order.
In some cases, the average cost to treat for a diagnosis may be close to an expected reimbursement for the diagnosis. In other cases, the average cost to treat may vary substantially from the expected reimbursement. Where both average cost to treat and expected reimbursement are available, both information points may be valuable to the health care provider. All this information is input into the system 100 (e.g., via one or more of the devices 104-110, 116) and is associated with the patient's electronic medical record(s) (which may be stored in the database 114), as described herein.
Once a patient is admitted, various costs are aggregated based on the care ordered for or provided to the patient. For example, intravenous (IV) fluids may be ordered for the patient. There is a cost to the hospital for the fluids. There is an additional cost to the hospital for nursing care associated with setting up and administering the IV fluids. As another example, an antibiotic may be ordered for the patient. There is a cost to the hospital for the antibiotic. In addition, the hospital room in which the patient visit is associated with a cost. Each of these costs is included in a running schedule or running total of costs associated with the patient's hospital visit. In conventional systems, while these costs may be predetermined, the costs may not be readily available to a health care provider. In contrast, in the system 100, the orders for the IV fluids and antibiotic may be entered, and the effect of those costs for those items against the overall reimbursement or average cost to treat may be seen and evaluated before they are even administered.
The progress bar 304 may represent activity related to value continuum 301. A left (green) end of the progress bar 304 may be associated with zero cost (i.e., little or no activity related to the value continuum 301). The right (red) end of the progress bar 304 may represent the expected reimbursement or average cost to treat for the medical procedure. In effect, then, the progress bar represents progress toward reaching an expected reimbursement or average cost to treat for the medical procedure (as disclosed herein, the average cost to treat, the expected reimbursement, and hence the progress bar 304 and value continuum 301 may increase (or in some cases decrease) during a patient's visit). The green region 304a indicates that the aggregated costs of care are within the reimbursement or average cost window, and may be referred as “high value” or “premium value.” The yellow region 304b may indicate that costs are starting to approach or exceed expected reimbursement or average cost to treat (referred to as “moderate value”). The red region 304c may indicate that costs are exceeding expected reimbursement or average cost to treat, and the care may no longer be good value (referred to as “low value”). Thus, a typical (average) patient treatment plan may conclude with the aggregated costs approximately in the center of the yellow region 304b.
Each time a cost is added for the patient, the progress bar 304 may be updated to reflect the additional aggregated cost. For example, when a physician orders an antibiotic for a patient, the costs associated with that care are determined, and the effect of those costs relative to the overall reimbursement or average cost to treat may be indicated in real-time by a change in the fill level (shown in
As shown in
In some embodiments, different aggregated or projected costs may affect the movement of the indicator 406 on the progress bar 404 at different times. For example, orders (e.g., cardiology, laboratory, medications, therapy consults, radiology, etc.) entered through a computerized physician order entry (CPOE) system (see for example,
While the physician charges and costs are accrued and billed separately, facility charges and costs are typically a direct result of physician orders. These facility charges may include:
The comparison with the overall reimbursement or average cost to treat may account for different financial factors, including profit margins, “fudge factors”, differences between insurance providers, seasonal variations of costs, and the like. For example, if an average cost to treat a particular diagnosis is $5000, but it is known that certain costs increase by approximately 10% during a particular time of year, the average cost to treat may be adjusted to $5500 before it is used as the target in the progress bar 404. Such adjustments may be made in a cost database, e.g., by a facility accountant or system administrator.
In some embodiments, the progress bar 404 may reflect an anticipated cost at discharge. The anticipated cost at discharge may be determined based on a number of factors, such as how long the patient has been admitted, the DRG, ICD-9 or ICD-10 codes, the costs aggregated up to a current point in time, and the like. Once determined, the anticipated cost at discharge may be displayed on or with the progress bar 404. The anticipate cost at discharge may serve as a “look ahead” feature that allows a health care provider to compare a current patient's costs against cost trends from similar patients to show how the current patient costs are tracking.
In some embodiments, the average length of a visit for a procedure is also presented on the display 400, e.g., in proximity to the progress bar 404. The displayed average length of visit for a DRG may be used by the health care provider, along with the progress bar 404, to help the health care provider plan the patient care. For example, the average length of visit gives the health care provider an estimated endpoint of care, so that the health care provider may start to generate a discharge plan, consider or schedule resources (rooms, nurses, etc.), and the like. Also, the estimated length of a visit may influence the health care provider's decisions on care. For example, if an average length of a visit for an appendectomy is one night, and a particular health care provider regularly keeps patients with the same diagnosis for two nights, the health care provider may consider a change his plan of care if the provider sees on the display 400 that the average visit is one night and his standard care plan is outside the norm.
The system 100 may be used for cost comparisons. For example, if a patient experiences respiratory problems while in the hospital, the health care provider may determine that an x-ray or computerized axial tomography (CAT) scan is needed. The health care provider may provisionally enter an order for an x-ray on the display 400 and then view the movement of the progress bar 404 to see how the x-ray affects the overall value continuum. The health care provider may then provisionally enter an order for a CAT scan and then view the movement of the progress bar 404 to see how the CAT scan affects the overall value continuum. Because the cost of a CAT scan is so much higher than the cost of an x-ray, it is likely that the progress bar 404 would move closer to red due to the CAT scan than it would due to an x-ray. By comparing the movement of the progress bar 404 for each test before the test is ordered, the health care provider may better understand the financial impact of each test or order on the patient's treatment plan.
The system 100 also may be used in early decision making by the health care provider. Consider that a health care provider creates an order that may have some cost variability. For example, an order for physical therapy may have widely varying costs, depending on the number of sessions, the progress of the therapy, the condition of the patient, and the like. In some embodiments, the system 100 may be configured to display an estimated reimbursement or an estimated average cost for the order based on the diagnosis before the order is finalized. The estimated reimbursement or average cost may be displayed in the system 100 in real time while the order is being filled to give the health care provider an indication of what an order will cost. The health care provider then may use those estimates in his decision making. As the order is filled and actual costs are incurred, the costs may be compared to the estimated average cost or reimbursement. In some embodiments, the actual costs also may be used to update the estimate for later procedures. Scheduled procedures may be handled in a similar manner. The cost for a scheduled procedure may be estimated at the time the procedure is scheduled based on a historical average cost to perform the procedure on patients with the same diagnosis. In situations where a DRG is not available, ICD-9 or ICD-10 codes may be used, or an estimated cost for a procedure may be determined based on costs for the procedure across an entire patient population or the average cost for the physician performing the procedure based on having performed the same procedure in the past.
In some embodiments, the process and metrics will be driven by the physician, since the physician is the health care provider who admits patients. The physician may have an overall value metric assigned to him. The overall value metric may be based on an aggregation of overall value continuums for a plurality (e.g., some, most, or all) of the medical visits, procedures, or diagnoses for which the physician is the attending health care provider. In other embodiments, health care providers other than a physician may admit the patient.
A specialist health care provider who provides services during a procedure (e.g., an anesthesiologist during a surgery) may bill separately for his professional services; thus, the fee for the specialist may not be included in the overall value continuum for a procedure. However, the resources of the facility that are used by the specialist may affect the overall value continuum. For example, one anesthesiologist may require multiple attempts to intubate, or may keep patients on a ventilator longer than other anesthesiologists, or may use more expensive anesthesia or in greater quantities than other anesthesiologists. Those costs will be incurred by the facility and will affect the overall value continuum for that procedure.
In some embodiments, consultations with other health care providers (e.g., other physicians, such as specialists) may be included in the determination of value, as shown in the value continuum and corresponding progress bar 304. Each health care provider may have an overall value metric assigned to him. When a health care provider in charge prepares to consult another health care provider, the health care provider in charge may review the overall value metric associated with the consultant to determine if the consultant represents a good value. By examining value metrics for multiple consultants, the health care provider in charge may determine which consultant represents the best value.
The system 100 may include one or more reporting applications or modules for reporting on value continuums. Reporting may be available to determine an overall value of each cost center (e.g., pharmacy, nurse, physician, caregiver in charge, consultant caregiver, lab, and the like) based on different parameters. The data in the reports may be grouped for a particular period; for a particular type of procedure, hospitalization, or diagnosis; for a particular clinic or hospital in a multi-facility hospital chain; or for any other parameter or combination of parameters. For example, reporting features may allow a user to review the overall value for all internal medicine physicians who treated pneumonia between March and September at Hospital A. The data may be broken out by physician or the data may be grouped for the physician group. Grouped data may be selected and a “drill-down” option may be applied to see more specific data. For example, grouped data may show that a physician has a value metric for a six-month period for pneumonia patients. However, a drill down on the grouped data may indicate that the physician had high value for all patients in the six-month period except for one patient with special circumstances, which brought the physician's average value metric down. Trend reporting allows a user to review the value of a physician or other care provider at different points in time over a period.
The HVA server 502 may be a back-end server (similar to the server 112 of
The facility charge master data source 506A is a database, data table, or other data source that includes charge information for a hospital or other facility. The HVA server 502 stores or is able to access the charge information from the facility charge master data source 506A, and uses the information from the data source 506 to convert orders received from the EMR system 504 to one or more costs. In some embodiments, the facility charge master data source 506A may be received by the HVA server 502 as a file (e.g., via email). The file may then be loaded into the HVA server 502. Alternately, the HVA server 502 may connect directly to the hospital or facility accounting system to retrieve these charges. Ultimately, it is hospital or facility costs that are used in the system 500; these may be determined simply by multiplying a cost-to-charge ratio factor by the charges or have a table or method of calculating costs from the orders.
The EMR user interface client 503 may be implemented as software or hardware. In an aspect, the EMR user interface client 503 is accessed by physician provider device 501A to connect to the EMR system 504 and, by way of HVA client application 508, the HVA server 502.
The HVA server 502 connects to a hospital or facility contracting system to obtain accurate cost data based upon admitting diagnosis codes or DRG codes when they become available. Alternatively, the HVA server 502 may calculate the cost data itself, either from a statistical model fit to historical data or from a DRG cost calculator. If the HVA server 502 performs the calculations, then factors, rates, and formulae may be stored in the HVA server 502 for easy access. If a statistical model is used, then the HVA server 502 may act upon patient symptoms or diagnosis codes for input to the model.
The HVA server 502 may be configured with one or more data stores for use by the system 500 to support model development and displays. Such data that the system 500 supports includes:
Each HVA client application 508 may be accessed on a client device or end-user device with a display (such as one of the end user devices 104-110 of
Each HVA client application 508 may be installed on a client device (such as the EMR user interface client 503 or one of the end user devices 104-110 of
In an embodiment, the HVA client application 508 and the HVA server 502 communicate using a stateless transfer architecture and protocol, a part of which is shown logically in
The HVA server 502, in cooperation with the HVA client application 508, and other components of the system 500 of
The HVA Server 502 also executes the program 510 to develop or use specific models, to populate specific data stores, to analyze data using the models, and to interact with the HVA client application 508 and the EMR system 504. For example, the program 510 is executed to compute Measured Cost, which is a cost basis used to compare against a Baseline Cost. The Baseline Cost is derived from application of analytics models and cost models and various methods of the analytics engine 520. For example, an estimate and correct method may be used to derive the Measured Cost, such that any time actual costs to treat a patient exceed estimated costs to treat the patient, the actual cost to treat the patient is used in lieu of the estimated cost to treat according to: Measured Cost=max (Sum(Orders), Sum(Actuals)). To derive Sum(Orders) for every ordered/scheduled event the, the analytics engine 520 may be accessed to apply the following logic: for events that have a cost based on variables not known at the time of order, the cost will be estimated using a method defined in the analytics engine 520 (average cost from the analytics models) to approximate the following variables: Procedures: the measured cost=max (estimate for procedure, actuals for procedure); Therapies: the measure cost=estimated for therapies; Quantities (PRN): assume quantity=1; and Time: the maximum time duration is assumed. Total Cost is derived by comparing the Measured Cost against the Benchmark Cost for the diagnosis. Predicted Cost is derived by comparing the Measured Cost against the Expected Costs (from the analytics models) for the diagnosis and current length of treatment. Category Cost Totals are derived from partitioning the Measured Cost using a defined mapping based on revenue codes (from the analytics models: for example, Radiology, Lab, Procedure, Therapy, Pharma, Room, Other). Order Totals are derived from partitioning (disambiguating) the Measured Cost using charge codes and including a frequency metric (from the analytics models) for the diagnosis. In an example, the HVA Cost Model has five components, which may be .csv files that have formats and use data specified as follows. charge_codes.csv; PharmaNDCCodeCosts.csv; ChargeCodeCosts.csv; DRGAdjustedAverageCosts.csv; and category_thresholds.csv. The first three files may be applied to charge codes that are assigned to individual patient visits, the DRGAdjustedAverageCosts.csv file is referred to as the Baseline Cost, from which savings may be compared. The category_thresholds.csv file partitions or disambiguates the Baseline Costs into seven individual categories by DRG: Room, Lab, Procedure, Pharma, Therapy, Radiology, and Other.
To build the Baseline Costs, the HVA analytics engine 520 may execute instructions of the data intake engine 580 to access data from the EMR system 504. For example, the HVA analytics engine 520 populates a number of tables in a local data store, including Populate the hospital_pharma_costs table. This process involves reading data directly from the EMR system 504. The first step involves running valuation program HVAAnalytics, which may be a .jar executable, for example) on the HVA analytics engine 520 using the flag: processARangeOfEMRIntakes=true to produce a very large file, PharmaExportData.csv. This very large file includes any corrections for pharma charge codes seen in the EMR database. This file may be exported and uploaded into the hospital_pharma_costs table using the command:
In an embodiment, the HVA client application 508 enables a display that is the same as or similar to the display 300 of
The system 500 operates in real-time or nearly real-time, such that changes to data in various components of the system 500 may be reflected in other components concurrently or within a short period after the change. For example, whenever data from the EMR system 504 for a patient record that is currently on display at the HVA client application 508 is updated with new information relating to either the DRG or the orders/costs associated with the patient, the system 500 becomes aware of the data changes within a short period (e.g., 15 seconds) of the change and presents updated HVA value content on the display of the HVA client application 508. Example mechanisms to “make the system 500 aware” are disclosed herein, including with respect to the description of
Components of the system 500 may monitor changes in the treatment plans by periodically comparing the latest measured values against the baselines. The components may use configurable threshold ranges to define notification events that may be sent to a subscribing endpoint (by, for example email, message queues, http, etc.). Example endpoints shown in the system 500 of
To provide an alerting function (such as display 830 of
In some embodiments, when the HVA client application 508 displays comparison data (i.e., the value continuum and the corresponding progress bar) for a patient, the HVA client application 508 may display data comparisons in one of several different modes. The activity surrounding the patient during a displayed admission cycle may cause the progress bar to move from green to yellow to red. The user may select the type of comparison the user wishes to see, including:
In some embodiments, the system 500 may provide feedback on orders that are placed for a patient. The feedback may relate to the practices of other physicians treating patients with the same or similar diagnosis, and be based on historical information. Such historical information may be gathered over time for a particular facility, a group of facilities, a group of physicians, or any other suitable group that shares at least one characteristic. For example, if a physician orders an x-ray for a patient, the system 500 may inform the physician how frequently that x-ray order is associated with treating that diagnosis. In some embodiments, for orders that are very common with the patient's diagnosis, the system 500 might not generate an alert, but for orders that are comparatively rare (e.g., other physicians order the x-ray less than 5% of the time, or less than 20% of the time, or any other suitable threshold), the system 500 generates an alert. The alert may be displayed at the HVA client application 508, and may be similar to the following: “For patients with this diagnosis, the x-ray order is only seen in 3% of the treatment plans.” Similarly, the system 500 may provide feedback on orders based on best practice treatment protocols for a diagnosis. Some hospitals, facilities, and provider groups have developed best practice treatment protocols for each diagnosis. In such cases, the system 500 may provide an alert if an order is outside the predetermined protocol.
In some embodiments, the system 500 may provide information about orders commonly associated with a particular diagnosis. Such information may relate to the practices of other physicians treating patients with the same or similar diagnosis, and be based on historical information. For example, if a patient is assigned a diagnosis of pneumonia, the system 500 can inform the physician what are the most common orders prescribed for patients with a diagnosis of pneumonia. In some embodiments, the orders may be ranked by how frequently the orders are associated with treating the diagnosis (i.e., frequency of use) or by category of care (e.g., labs, radiology, etc.). As a particular example, the orders may be presented as a list that is ordered by rank and is displayed at the HVA client application 508. As another example, the orders may be grouped by day or other period during a length of a visit or a length of care (e.g., most common orders for Day 1 of a hospital visit, most common orders for Day 2 of the hospital visit, etc.). In some embodiments, information about orders may be related to a total cost to treat. For example, the system 500 may inform the physician which orders have been historically associated with patients whose total cost to treat was less than an average cost to treat, as a way of indicating that such orders are associated with good outcomes. In some embodiments, the physician may select orders directly from the displayed list.
In some embodiments, when a patient is discharged, a communication may be sent to the HVA server 502 so that an end of a visit may be recorded for the patient. Once this event occurs, further communications from the EMR system 504 may not be needed for this patient. The system 500 may maintain a persistent HVA value analysis for a discharged patient (e.g., at a database in the HVA server 502).
The progress bar is displayed in the HVA client application 508 based on the expected reimbursement or average cost to the hospital or facility to treat the patient; this cost is based on the diagnosis for the patient. It is common for the DRG to change throughout the facility visit period. In such cases, the progress bar displayed in the HVA client application 508 may be updated to reflect the change whenever a new DRG code is received for a patient. Similarly, the average cost to treat may be modified at one or more points during a patient visit based on how the patient progresses, the outcome of one or more procedures, and the like.
In some cases, a working DRG code and illness severity may not be available right away when a patient is admitted to the hospital or facility. In fact, it may be many hours or even days later before even a working DRG code is known. In some embodiments, the HVA client application 508 may indicate that no DRG is currently available for this patient. In some embodiments, the system 500 may use a generic baseline DRG or a baseline diagnosis that is discerned from initial evaluation of patient symptoms.
Because some payment reform models are trending toward a single lump sum payment to a facility that includes health care provider fees, in some embodiments, the average cost to treat may include both facility costs and health care provider (e.g., physician) fees. Additionally, from that single payment, physicians and other health care workers may need to negotiate their fees with the facility. The system 500 may facilitate a “share in savings” model where the physician fees are based on the value (cost versus reimbursement) the physician provided to the patient.
Although
At step 601, the system 500 determines an average cost to treat, an expected reimbursement, or both, for a DRG associated with a patient. This may include, for example, the HVA server 502 calculating the average cost to treat based on an average cost of treatment for all patients having the same diagnosis that are treated by a predetermined group of physicians (e.g., the physicians affiliated with the health care facility) over a predetermined historical period (e.g., the two previous years) or at a predetermined group of health care facilities over a predetermined historical time period. Additionally, or alternatively, this may include the HVA server 502 calculating the average cost to treat based on a designed plan of care for the DRG.
At step 603, the system 500 receives an indication of one or more health care services provided or scheduled for the patient. This may include, for example, a health care provider (e.g., a physician) entering one or more orders into the CPOE system and then the HVA server 502 receiving the order or an indication of the order from the EMR system 504.
At step 605, the system 500 determines a cost for each of the health care services. This may include, for example, the HVA server 502 obtaining the cost(s) from the facility charge master 506 or calculating the cost(s) based on information from the facility charge master 506.
At step 607, the system 500 then aggregates the costs for the health care services to determine a total aggregated cost. This may include, for example, the HVA server 502 adding each of the individual costs together.
At step 609, the system 500 configures an indicator to indicate the total aggregated cost relative to the average cost to treat or the expected reimbursement, and then displays the indicator to a user. This may include, for example, the HVA server 502 configuring a progress bar, such as the progress bar 304 or the progress bar 404. Once the progress bar is configured for display, a client application, such as the HVA client application 508 may display the progress bar.
Steps 603-609 may be repeated as the health care provider enters new orders or new costs are aggregated. All operations described in the method 600 may be performed in real-time in to provide a real-time display to a user as patient orders are entered and costs are aggregated.
Although
In block 725, the HVA client application 508 scrapes a Visit ID (or, simply, a visit) of the selected patient, and in block 730 the HVA server 502 receives the Visit ID for use in further processes under operation 700. For example, in block 735, the HVA server 502 determines, based on the visit, if the selected patient has a valid working DRG. If the selected patient does not have a valid working DRG, the operation 700 moves to block 740 and the HVA server 502 responds to the request 507 to show at the HVA client application 508 display, a grey bar with a note that the selected patient does not have a working DRG (the working DRG may be created by execution of other operations such as the physician provider device 501A accessing the CPOR module 504A to enter orders and the CDI specialist device 501B entering appropriate medical codes. The operation 700 then moves to block 799 and ends. In block 735, if the selected patient does have a valid working DRG, the operation 700 moves to block 745, and the HVA server 502 provides information to the HVA client application 508 to cause display of a value continuum and a corresponding progress bar populated with data extracted by the HVA server 502 from the EMR system 504. Following block 745, the operation 700 then proceeds to block 745A or 745B, depending on a request (signal) from the HVA client application 508. In block 745A, the HVA client application 508 receives an activity signal generated by hovering of a cursor or other pointing device over the progress bar displayed through the HVA client application 508, and sends a minimal request 507 to the HVA server 502. In response, the HVA server 502 determines if information related to the patient and the patient's treatment plans is available and, if so, provides information and instructions (block 750) that causes the HVA client application 508 to display a tool tip (see
When the expanded progress bar (
The operation 700 of
Aspects of operation of the system 1000 differ from those of the system 500 of
Aspects of operation of the system 1100 may differ from operation of the system 500 of
Any of the systems of
The disclosed embodiments are also particularly useful for prepaid or bundled medical services, including, but not limited to, health maintenance organizations (HMOs) and clinically integrated networks (CINs). In these environments, the disclosed progress bar may track costs for a defined period against a contracted prepaid or bundled amount. As services are deployed and resources are consumed, a health care provider may quickly see exactly how the provider is performing in the value of care continuum for each patient with prepaid or bundled medical services.
As described above, embodiments of this disclosure provide the ability to link the cost side of patient care at the point of the provider with the reimbursement side of the patient care from the third party payer. Once the expected reimbursement is determined, that information will be entered into the system. The disclosed embodiments also provide the ability to link actual costs with estimated average costs to treat. As the primary driver of cost, the physician or other health care provider is able to monitor in relative terms or in precise terms the cost of his care during each phase of the care continuum. By linking the physician with these financial components, improved awareness and greater value for care provided will result in finally bending the cost of the health care curve downward.
In some embodiments, various functions described above are implemented or supported by a computer program that is formed from computer readable program code and that is embodied in a computer readable medium. The phrase “computer readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer readable medium” includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a compact disc (CD), a digital video disc (DVD), or any other type of memory. A “non-transitory” computer readable medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer readable medium includes media where data may be permanently stored and media where data may be stored and later overwritten, such as a rewritable optical disc or an erasable memory device.
It may be advantageous to set forth definitions of certain words and phrases used throughout this patent document. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable computer code (including source code, object code, or executable code). The terms “transmit” and “receive,” as well as derivatives thereof, encompass both direct and indirect communication. The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation. The term “or” is inclusive, meaning and/or. The phrase “associated with,” as well as derivatives thereof, may mean to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The phrase “at least one of,” when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, “at least one of: A, B, and C” includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C.
While this disclosure has described certain embodiments and generally associated methods, alterations and permutations of these embodiments and methods will be apparent to those skilled in the art. Accordingly, the above description of example embodiments does not define or constrain this disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of this disclosure, as defined by the following claims.
This application is a continuation-in-part of U.S. patent application Ser. No. 15/350,910, entitled “SYSTEM AND METHOD FOR DETERMINING AND INDICATING VALUE OF HEALTH CARE,” filed Nov. 14, 2016, which is a continuation in part of U.S. patent application Ser. No. 15/177,058 entitled “SYSTEM AND METHOD FOR DETERMINING AND INDICATING VALUE OF HEALTH CARE,” filed Jun. 8, 2016. The contents of the above-identified patent document is incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15350910 | Nov 2016 | US |
| Child | 15590382 | US | |
| Parent | 15177058 | Jun 2016 | US |
| Child | 15350910 | US |
