Patent Application
20200143943
This disclosure generally relates to decision support systems, and more specifically relates to a system that provides notifications of variances in decisions.
Experts and professionals are subject to the same life conditions as the average person: stress, fatigue, life-disrupting events, distractions, etc. These life conditions can lead to decisions that are not consistent with their normal practice, or in some cases, even inconsistent with what a consensus of other experts would provide.
A decision support engine allows defining multiple events and corresponding actions for those events. An event could be, for example, a decision that is at variance with what the professional usually suggests, or at variance with standard practice of other professionals. Suitable action can be taken when an event occurs. Examples of suitable actions include, for example, to notify the professional, to notify the customer or patient, to notify an administrator, and to log all data related to the decision that caused the event. The decision support engine receives biometric input from one or more biometric sensors worn by the professional, and can thus log the physical state of the professional at the time the event occurs. Both conforming and non-conforming decisions can be logged to a profile maintained for the professional, along with the corresponding biometric data. For each event, the professional's biometric data is logged and can be analyzed to determine statistical correlations between the events corresponding to the professional and the professional's physical state.
The foregoing and other features and advantages will be apparent from the following more particular description, as illustrated in the accompanying drawings.
The disclosure will be described in conjunction with the appended drawings, where like designations denote like elements, and:
The disclosure and claims herein are directed to a decision support engine that allows defining multiple events and corresponding actions for those events. An event could be, for example, a decision that is at variance with what the professional usually suggests, or at variance with standard practice of other professionals. Suitable action can be taken when an event occurs. Examples of suitable actions include, for example, to notify the professional, to notify the customer or patient, to notify an administrator, and to log all data related to the decision that caused the event. The decision support engine receives biometric input from one or more biometric sensors worn by the professional, and can thus log the physical state of the professional at the time the event occurs. Both conforming and non-conforming decisions can be logged to a profile maintained for the professional, along with the corresponding biometric data. For each event, the professional's biometric data is logged and can be analyzed to determine statistical correlations between the events corresponding to the professional and the professional's physical state.
Referring to
Main memory 120 preferably contains data 121, an operating system 122, and a decision support engine 123. Data 121 represents any data that serves as input to or output from any program in computer system 100. Operating system 122 is a multitasking operating system, such as AIX or LINUX. Decision support engine 123 defines multiple events and corresponding actions. The decision support engine 123 receives data from many sources, including biometric data corresponding to professionals, and determines when a decision varies enough to cause one of the events. When an event occurs, the event and corresponding physical state of the professional is logged.
The decision support engine 123 includes professional profiles 124, a safety monitor tool 125, a field collection and analysis tool 126, a notification tool 127, and one or more knowledge bases 128. The professional profiles 124 may include any suitable information relating to a professional. Professional profiles 124 may include, for example, events and the professional's corresponding physical state when the event occurs. The safety monitor tool 125 receives biometric data for one or more professionals. The biometric data for a professional can be logged when an event occurs. The field collection and analysis tool 126 includes one or more input sensors that log sensor data corresponding to a professional, a patient, or the environment. The notification tool 127 provides one or more prescribed notifications when an event occurs. Knowledge base(s) 128 can include any suitable database of information that could be accessed by the decision support engine. Suitable examples of knowledge bases 128 could include, for example, a knowledge base that includes work and rest regulations for professionals; a medical cases knowledge base that includes symptoms and usual treatments for those symptoms; and a medical professional case handling knowledge base that includes logged diagnoses and treatments, and may optionally include one or more logged conditions corresponding to the logged decisions.
Computer system 100 utilizes well known virtual addressing mechanisms that allow the programs of computer system 100 to behave as if they only have access to a large, contiguous address space instead of access to multiple, smaller storage entities such as main memory 120 and local mass storage device 155. Therefore, while data 121, operating system 122, and decision support engine 123 are shown to reside in main memory 120, those skilled in the art will recognize that these items are not necessarily all completely contained in main memory 120 at the same time. It should also be noted that the term “memory” is used herein generically to refer to the entire virtual memory of computer system 100, and may include the virtual memory of other computer systems coupled to computer system 100.
Processor 110 may be constructed from one or more microprocessors and/or integrated circuits. Processor 110 executes program instructions stored in main memory 120. Main memory 120 stores programs and data that processor 110 may access. When computer system 100 starts up, processor 110 initially executes the program instructions that make up operating system 122. Processor 110 also executes the decision support engine 123.
Although computer system 100 is shown to contain only a single processor and a single system bus, those skilled in the art will appreciate that a decision support engine as described herein may be practiced using a computer system that has multiple processors and/or multiple buses. In addition, the interfaces that are used preferably each include separate, fully programmed microprocessors that are used to off-load compute-intensive processing from processor 110. However, those skilled in the art will appreciate that these functions may be performed using I/O adapters as well.
Display interface 140 is used to directly connect one or more displays 165 to computer system 100. These displays 165, which may be non-intelligent (i.e., dumb) terminals or fully programmable workstations, are used to provide system administrators and users the ability to communicate with computer system 100. Note, however, that while display interface 140 is provided to support communication with one or more displays 165, computer system 100 does not necessarily require a display 165, because all needed interaction with users and other processes may occur via network interface 150.
Network interface 150 is used to connect computer system 100 to other computer systems or workstations 175 via network 170. Computer systems 175 represent computer systems that are connected to the computer system 100 via the network interface 150 in a computer cluster. Network interface 150 broadly represents any suitable way to interconnect electronic devices, regardless of whether the network 170 comprises present-day analog and/or digital techniques or via some networking mechanism of the future. Network interface 150 preferably includes a combination of hardware and software that allows communicating on the network 170. Software in the network interface 150 preferably includes a communication manager that manages communication with other computer systems 175 via network 170 using a suitable network protocol. Many different network protocols can be used to implement a network. These protocols are specialized computer programs that allow computers to communicate across a network. TCP/IP (Transmission Control Protocol/Internet Protocol) is an example of a suitable network protocol that may be used by the communication manager within the network interface 150. In one suitable implementation, the network interface 150 is a physical Ethernet adapter.
The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention.
The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.
Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device.
Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention.
Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
The medical decision support engine 123 preferably queries databases referred to herein as knowledge bases 128, which can include a work/rest regulations knowledge base 250, a medical cases knowledge base 260, and a medical profession case handling knowledge base 270. The work/rest regulations knowledge base 250 could be, for example, a database for a hospital that specified hospital policies regarding number of hours a medical professional is allowed to work within a given time period, required hours of sleep between shifts, number of consecutive shifts allowed, etc. The medical cases knowledge base 260 preferably includes a database of symptoms and acceptable diagnoses and treatments for those systems. The medical cases knowledge base 260 most preferably represents medical cases and corresponding symptoms, diagnoses and treatment from a large number of medical professionals, such as thousands or tens of thousands. The medical professional case handling knowledge base 270 includes medical cases, with their corresponding symptoms, diagnoses and treatments, for medical professionals that have a professional profile 124 in the medical decision support engine 280. The medical professional case handling knowledge based 270 preferably includes logged conditions for diagnoses and treatments 272. The logged conditions for diagnoses/treatments can include biometric data 214 received from the health monitor tool, as well as sensor data 230 received from the field collection and analysis tool 126. In this manner a medical professional's diagnoses and treatments are tied to the physical condition of the medical professional when the diagnoses and treatments were made, thereby allowing statistical analysis to be performed to determine whether there are correlations between variances in the diagnoses and treatments of a medical professional and the physical state of the medical professional, as indicated by the corresponding biometric data and sensor data.
The safety monitor tool 125 receives biometric data 214 from one or more wearable biometric sensors worn by professionals. One specific embodiment of safety monitor tool 125 in
Examples of suitable biometric data 214 that could be collected for medical professionals are shown in
Referring again to
Examples of suitable sensor data 230 that can be generated by the input sensors 220 are shown in
Audio streams/logs 540 can be analyzed to determine speech speed log 542, speech volume log 544, speech tone log 546, words spoken by the professional 548, words spoken by the patient 550; and the length of conversation 552. Of course, other data not specifically identified in
The decision support engine 123 shown in
Conforming diagnoses/treatments 650 are those diagnoses and treatments by the medical professional that were not at variance with accepted diagnoses and treatments, and which resulted in good results for the patient. Bad diagnoses/treatments 660 are those diagnoses by the medical professional that were at variance with accepted diagnoses and treatments, and which resulted in bad results for the patient. Note a variance in a diagnosis or treatment does not mean the diagnosis or treatment is a bad diagnosis or treatment, because the medical professional may be intentionally varying from accepted standards, believing the circumstances of the patient justify a different approach. The professional profile 610 thus could include a third category of diagnoses and treatments not shown in
Admin/Disciplinary action 670 can indicate whether the medical professional has had any administrative or disciplinary action by any suitable entity, including the medical professional's current employer, or any suitable association or organization. Current job duties 680 specify the job duties of the medical professional. Thus, the certifications/qualifications for a medical professional might specify the medical professional is a trauma nurse, while the current job duties 680 might indicate duties other than emergency room trauma. Recent hours worked 690 could be from a database that shows the shifts the medical professional has recently worked. Recent sleep 692 could be from a sleep log, such as 350 in
Referring to
An event can specify to take any suitable action when the event occurs. Examples of suitable actions 810 are shown in
A method 900 in
Various types of events could be defined within the scope of the disclosure and claims herein. Referring to
Instead of defining a severity level and corresponding actions for each event, as shown in
Method 1400 in
The results of a diagnosis or treatment that caused an event can be fed back to the system for future use. Referring to
The ability to correlate both biometric and sensor data with events makes it possible to “score” the medical professional according to their current health state, providing a numerical indicator of the physical condition of the medical professional at the time the diagnosis or treatment was made. Referring to
In addition to generating a health score for a medical professional for each event, an overall competency score can be generated based on data in the medical professional's profile relating to conforming and non-conforming diagnoses and treatments, such as 650 and 660 in
Because the biometric and sensor data is logged for each event, this logged data can be analyzed to determine any correlations that might exist. Referring to
The disclosure and claims herein support an apparatus comprising: at least one processor; a memory coupled to the at least one processor; and a decision support engine residing in the memory and executed by the at least one processor, the decision support engine comprising: a plurality of events that each comprises: a specification of at least one variance of a decision; and at least one corresponding action that includes providing a notification of the event to a person; a plurality of professional profiles that each corresponds to a plurality of professionals, wherein each of the plurality of professional profiles comprises decisions by the corresponding professional; a safety monitor tool that receives biometric data from biometric sensors worn by the plurality of professionals; wherein the decision support engine detects when one of the plurality of events occurs, and in response, provides the notification corresponding to the event to the person and logs the biometric data corresponding to the one professional that caused the one event to occur.
The disclosure and claims herein further support an apparatus comprising: at least one processor; a memory coupled to the at least one processor; and a medical treatment analysis engine residing in the memory and executed by the at least one processor, the medical treatment analysis engine comprising: a plurality of severity levels; a plurality of events that each comprises: a specification of at least one variance of a diagnosis or treatment; one of the plurality of severity levels; and at least one corresponding action that includes providing a notification of the event to a person; a plurality of professional profiles that each corresponds to a plurality of medical professionals, wherein each of the plurality of professional profiles comprises diagnoses and treatments by the corresponding medical professional, recent hours worked, recent sleep, recent events, and recent medications; a health monitor tool that receives biometric data from biometric sensors worn by the plurality of medical professionals, wherein the biometric data comprises heart rate, body temperature and a sleep log for the one medical professional that caused the one event to occur; a plurality of input sensors comprising video cameras, audio input devices and data input monitors that monitor interaction of the plurality of medical professionals with a plurality of patients; wherein the medical treatment analysis engine receives sensor data from the plurality of input sensors, wherein the sensor data comprises video streams, audio streams and typing speed; wherein the medical treatment analysis engine queries a medical cases knowledge base that correlates diagnoses with corresponding treatments and further comprising a work and rest regulations knowledge base that specifies regulations regarding amount of work and rest for medical professionals; wherein the medical treatment analysis engine queries a medical professional case handling knowledge base that includes a plurality of diagnoses and treatments, and for each diagnosis, corresponding biometric data for a medical professional that made the diagnosis, and for each treatment, corresponding biometric data for a medical professional that gave the treatment; wherein the medical treatment analysis engine detects when one of the plurality of events occurs, and in response, provides the notification corresponding to the event to the person and logs the biometric data corresponding to the one medical professional that caused the one event to occur, wherein the notification of the event to the person comprises at least one of: notifying the medical professional; notifying a patient corresponding to the event; and notifying an administrator.
The disclosure and claims herein additionally support a computer-implemented method executed by at least one processor for detecting variance in decisions by professionals, the method comprising: defining a plurality of events that each comprises: a specification of at least one variance of a decision; and at least one corresponding action that includes providing a notification of the event to a person; providing and maintaining a plurality of professional profiles that each corresponds to a plurality of professionals, wherein each of the plurality of professional profiles comprises decisions by the corresponding professional; receiving biometric data from biometric sensors worn by the plurality of professionals; detecting when one of the plurality of events occurs, and in response: providing the notification corresponding to the event to the person; and logging the biometric data corresponding to the one professional that caused the one event to occur.
A decision support engine allows defining multiple events and corresponding actions for those events. An event could be, for example, a decision that is at variance with what the professional usually suggests, or at variance with standard practice of other professionals. Suitable action can be taken when an event occurs. Examples of suitable actions include, for example, to notify the professional, to notify the customer or patient, to notify an administrator, and to log all data related to the decision that caused the event. The decision support engine receives biometric input from one or more biometric sensors worn by the professional, and can thus log the physical state of the professional at the time the event occurs. Both conforming and non-conforming decisions can be logged to a profile maintained for the professional, along with the corresponding biometric data. For each event, the professional's biometric data is logged and can be analyzed to determine statistical correlations between the events corresponding to the professional and the professional's physical state.
One skilled in the art will appreciate that many variations are possible within the scope of the claims. Thus, while the disclosure is particularly shown and described above, it will be understood by those skilled in the art that these and other changes in form and details may be made therein without departing from the spirit and scope of the claims.
