Patent Publication Number: US-2022238195-A1

Title: System and method of processing medical implant device and patient data

Description:
TECHNICAL FIELD 
     The present disclosure relates to a method, apparatus, and computer-readable medium for selecting medical implant devices for preoperative patients and/or connecting preoperative patients with a third party that has personal experience with the medical procedure for which a preoperative patient is preparing. Exemplary embodiments of the present disclosure relate to data processing of medical implant device data and otherwise facilitating or enabling informed medical procedures. 
     BACKGROUND 
     Medical care and the surgical implant of medical devices pose many decisions to the preoperative patient. Determining the appropriate medical implant device for a preoperative patient involves determining, inter alia, the preoperative patient&#39;s current health, risk factors, health goals, and the medical devices available. Health professionals in a preoperative patient&#39;s surgical support team may be constrained by time and/or experience and may be unable to provide preoperative patients with answers to technology-specific questions, post-operation expectations, and first-hand information concerning the recovery process. For example, communication between surgeons and post-operative patients may be sub-optimal and/or short in duration, and communication between surgeons and medical device manufacturers may be sub-optimal or otherwise not collaborative. These limitations produce an information deficit which can negatively affect a preoperative patient&#39;s surgical outcome. Therefore, there is a need for a system and method operable to enable, or otherwise facilitate, preoperative patients to make informed medical decisions. 
     SUMMARY 
     The present disclosure provides for a method, apparatus, and computer-readable medium for processing data. 
     In a first exemplary embodiment, a method of processing medical implant device data for preoperative patients includes storing, by a computer memory, a first list of medical implant devices. The method further includes assigning, by a processor in communication with the computer memory, one or more device-variables to each of the plurality of medical implant devices. The method of processing medical implant device data additionally includes storing, by the computer memory, one or more queries assigned to the one or more device-variables. Further, connecting a client computer with the processor and transmitting to the client computer the one or more queries. The method further includes receiving, by the processor, one or more data inputs from the client computer in response to the one or more queries, generating, by the processor, a second list of medical implant devices as a function of the one or more data inputs received, and transmitting the second list of medical implant devices to the client computer. 
     In a second exemplary embodiment, a method of connecting a patient and a patient partner includes storing, by a server having a memory and a processor, datasets of a plurality of patient partners. The method further includes connecting a client computer with said server and transmitting one or more queries to the client computer. The method of connecting a patient and a patient partner additionally include receiving, by the processor, one or more data inputs from the client computer in response to the one or more queries. Further, the method includes generating, by the processor, a list of patient partners as a function of the data inputs and transmitting the list of patient partners to the client computer. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings are incorporated herein as part of the specification. The drawings described herein illustrate embodiments of the presently disclosed subject matter and are illustrative of selected principles and teachings of the present disclosure. However, the drawings do not illustrate all possible implementations of the presently disclosed subject matter and are not intended to limit the scope of the present disclosure in any way. 
         FIG. 1  presents a simplified diagram of the system environment according to an exemplary embodiment of the present disclosure. 
         FIG. 2  presents a flow chart of a method of processing medical implant device data according to an exemplary embodiment of the present disclosure. 
         FIGS. 3A and 3B  present simplified diagrams of client computers according to exemplary embodiments of the present disclosure. 
         FIGS. 4A-4B  present flow charts of a method of processing patient partner data and surgeon data according to an embodiment of the present disclosure. 
         FIG. 4C  presents a flow chart of a method of processing patient partner data according to an embodiment of the present disclosure. 
         FIG. 5  presents a flow chart of a method of patient feedback according to an embodiment of the present disclosure. 
         FIG. 6  presents a simplified diagram of a portion of the system environment according to an exemplary embodiment of the present disclosure. 
         FIGS. 7A-7C  present a flow chart of queries and data inputs corresponding to one or more medical implant device-variables according to an exemplary embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     It is to be understood that the invention may assume various alternative orientations and step sequences, except where expressly specified to the contrary. It is also to be understood that the specific assemblies and systems illustrated in the attached drawings and described in the following specification are simply exemplary embodiments of the inventive concepts defined herein. Hence, specific dimensions, directions, or other physical characteristics relating to the embodiments disclosed are not to be considered as limiting, unless expressly stated otherwise. Also, although they may not be, like elements in various embodiments described herein may be commonly referred to with like reference numerals within this section of the application. 
     Where they are used herein, the terms “first”, “second”, and so on, do not necessarily denote any ordinal, sequential, or priority relation, but are simply used to more clearly distinguish one step/element or set of steps/elements from another, unless specified otherwise. 
     Each year, thousands of surgical patients experience injuries or other medical concerns as a result of their medical implant devices. For each specific surgical procedure, the medical implant devices available provide patients with a widely varying post-operative experience. Different medical implant devices available for the same surgical procedure provide, inter alia, varying device longevity and expected complication rates, and enable patients to engage in different levels of post-operative activity. Selecting the appropriate medical implant device for each patient requires asking questions and having the necessary information to provide personalized answers. For example, making an informed selection of a medical implant device for a total knee replacement (i.e., knee arthroplasty) includes identifying the available knee implant devices, determining the preoperative patient&#39;s activity level, determining the preoperative patient&#39;s preference for newly developed technology, identifying the stability of the preoperative patient&#39;s knee, determining the preoperative patient&#39;s age, and determining the geographic availability of surgeons able to perform the surgical procedure with a specific knee implant device. Medical implant devices are not one size fits all and personalizing the selection of a patient&#39;s medical implant device reduces the potential for issues therewith. 
     Referring now to  FIGS. 1, 2, and 6 , presented is an exemplary embodiment of a method of medical implant device data processing  200 . The method  200  begins at block  202  by obtaining the technical data  106  and/or specifications of one or more medical implant devices from their original equipment manufacturers (OEMs). In an embodiment, the medical implant device technical data  106  is acquired from OEM web pages  104  and/or databases  104  by web data extraction and stored on one or more servers  102  (e.g., a first computer memory). Persons skilled in the relevant arts will recognize that additional methods of data acquisition may be utilized in conjunction with web data extraction, or instead of web data extraction, to obtain the medical implant device technical data  106 . For example, the medical implant device technical data  106  may also be obtained via manual data acquisition. 
     The method  200  continues at block  204  by storing a list of medical implant devices at the one or more servers  102 . For example, the list of the medical implant devices may include only those medical implant devices for which medical implant device technical data  106  was obtained in the previous step at block  202 . However, the list of medical implant devices may also include medical implant devices for which device data  106  has previously been downloaded, uploaded, or otherwise transferred to the one or more servers  102 . 
     At block  206 , the method  200  continues by generating one or more device-variables for each medical implant device in the list as a function of the medical implant device technical data  106 . For example, the device-variables may include, but are not limited to, device type, device material(s), device range of motion, device lifespan, patient gender, patient age, patient height, patient preexisting conditions, and device weight rating (e.g., acceptable patient weight range). In an embodiment, the device-variables are extracted or otherwise obtained from the medical implant device technical data  106 . The device-variables generated for the medical implant devices may also be produced as a function of a preexisting list of device-variables stored on the servers  102 . In an embodiment, not all device-variables of the preexisting list are applicable to all medical implant devices. For example, the device-variables generated at block  206  for knee arthroplasty implants may be different than the device-variables generated at block  206  for total hip arthroplasty implants. The method  200  continues at block  208  by assigning the device-variable values for each of the corresponding medical implant devices to each of the corresponding medical implant devices utilizing a processor  110  in signal communication with the servers  102 . 
     At block  210 , the method  200  includes storing one or more queries (e.g., questions) assigned to the one or more device-variables at the one or more servers  102 . As described below, assigning one or more queries to the device-variables facilitates filtering the available medical implant devices into a set of medical implant devices having technical specifications that meet the requirements of a particular patient. 
     At block  212 , the method of medical implant device data processing  200  continues by connecting a client computer  108 A,  108 B (e.g., a preoperative patient&#39;s smartphone, tablet, personal computer, or other computer device) with the one or more servers  102 . In an embodiment, the client computer  108 A,  108 B includes a visual display  120  or monitor operable to generate and display images to a user. As shown at block  214 , the method  200  continues by presenting the one or more queries  124  assigned to the device-variables to the preoperative patient in a predetermined sequence. In another embodiment, the queries  124  are not presented in a predetermined sequence. The display  120  of the client computer  108 A,  108 B may be utilized to present the queries  124 . However, persons skilled in the art will recognize that the client computer  108 A,  108 B may include other apparatuses operable to present the queries  124  to the preoperative patient. For example, the client computer  108 A,  108 B may include an audio loudspeaker  122  operable to produce the queries  124  in audible format. 
     The preoperative patient, through the client computer  108 A,  108 B, can answer the queries  124 . At block  216 , the method  200  continues by receiving, by the processor  110 , one or more data inputs from the client computer  108 A,  108 B in response to the one or more queries  124 . As illustrated in  FIGS. 3A-3B , in an embodiment, the queries  124  are presented as multiple choice questions with two or more alternative answers  126 A,  126 B,  126 C which the preoperative patient can select, thereby transmitting a data input from the client computer  108 A,  108 B to the processor  110 . In an embodiment, the preoperative patient may transmit a free-response answer to the processor  110  in response to each query  124 . Where a free-response answer is transmitted, the processor  110  may perform a keyword search to identify terms corresponding to the device-variables. 
     The method  200  continues at block  218  by generating, via the processor  110 , a second list of medical implants devices as a function of the one or more data inputs received at block  216 . For example, a query  124  may be assigned to the device-variable “range of motion,” and utilized in processing data concerning knee arthroplasty. The device-variable “range of motion,” may be categorized in the server  102  as small, medium, and large ranges of motion. In this example, medical implant devices utilized in total knee replacement might be considered to have a small range of motion at typical flexion of less than 115°, a medium range of motion at typical flexion of 116°-125°, and a large range of motion at typical flexion of greater than 126° after implantation. At block  210 , the query  124  assigned to the device-variable “range of motion” may be “Activity Level?”, and the data input received by the processor  110  from the client computer  108 A,  108 B may be one of the multiple choice answers “low”  126 A, “medium”  126 B, and “high”  126 C, with the answer “low”  126 A corresponding to small range of motion, “medium”  126 B corresponding to medium range of motion, and “high”  126 C corresponding to large range of motion. If the preoperative patient were to transmit the data input of the multiple choice answer “high”  126 C to the processor  110  via the client computer  108 A,  1086 , the processor  110  then generates a second list of medical implant devices as a function of the stored list of all knee implant devices that would be operable to provide the preoperative patient a large range of motion after implantation. 
     In an embodiment, at block  220 , the method  200  includes determining whether a data input has been received for each query  124 . If a data input has been received for each query  124 , the method  200  continues at block  222  by transmitting to the client computer  108 A,  1086  the second list of medical implant devices. If a data input has not been received for each query  124 , the method  200  returns to block  214  and transmits one or more queries  124  to the client computer  108 A,  108 B. 
     In an embodiment, at block  214  the queries  124  may be transmitted to the client computer  108 A,  108 B in a non-sequential manner (e.g., all at once). In such an embodiment, the data input received by the processor  110  would not necessarily be received in a specific order. At block  218 , when the method  200  generates a second list of medical implant devices, the queries  124  may be weighted such that certain data input is considered of higher value when the processor  110  generates the second list of medical implant devices. For example, the data input corresponding to a query  124  concerning the patient&#39;s material sensitivity/allergies may be weighted more than a query  124  concerning the patient&#39;s activity level, such that the second list generated by the processor  110  may not include all or any knee implant devices, for example, having a large range of motion after implantation. 
     In an embodiment, at block  214  the queries  124  may be transmitted to the client computer  108 A,  108 B in a sequential manner. In such an embodiment, the data input received by the processor  110  may be processed and a second list of medical implant devices generated as a function of the data input received in response to a first query  124 . A second query  124  may then be transmitted to the client computer  108 A,  108 B as a function of the second list. For example, where the first query  124  concerns the preoperative patient&#39;s metal sensitivity, and the corresponding data input indicates that patient has a metal sensitivity, the second list of medical implant devices suited for the patient&#39;s needs may not include any additional device-variables such as weight rating, age range, and/or preference for new technologies. Thus, the second list generated is transmitted to the client computer  108 A,  108 B at block  222 . However, if the corresponding data input indicates that patient does not have a metal sensitivity, the second list of medical implant devices suited for the patient&#39;s needs may include additional device-variables such as weight rating, age range, and/or preference for new technologies, and a second query  124  is transmitted to the client computer  108 A,  108 B at block  214 . 
     In an embodiment, as illustrated in  FIGS. 7A-7C , the queries  124  and data inputs corresponding to one or more medical implant device-variables at blocks  210 - 220  of the method  200  may comprise, but are not limited to, preoperative patient activity level  402 , preoperative patient material sensitivity  404 ,  410 ,  418  (e.g., metal sensitivity), preoperative patient age  412 A,  412 B, preoperative patient knee stability  414 , preoperative patient weight classification  406 , and preoperative patient preference for new technology  408 A,  408 B,  416 ,  420 . Additionally, the queries  124  may also concern the propensity of the joint in question to dislocate, graft type, and preference for a permanent or absorbable device/graft as a function of the medical procedure considered. 
     In an embodiment, the method of medical implant device data processing  200  includes an integrated user feedback component utilized to update the list of medical implant devices stored on the servers  102 . For example, after a predetermined period of time, and/or after receiving input from a patient that their surgical procedure has been completed, the processor  110  may transmit a query  124  to the client computer  108 A,  108 B comprising a multiple choice answer in the form of two or more levels of satisfaction with their medical implant device. Upon receiving the data input corresponding to the patient&#39;s level of satisfaction, the processor  110  amends a device-variable value corresponding to the device&#39;s ranking. As a result, medical implant devices in a list generated at block  218  may be listed in order of patient satisfaction. 
     Referring now to  FIGS. 1 and 4A-4B , presented is an exemplary embodiment of a method of data processing  300 . As indicated at block  302 , the method  300  includes storing a plurality of patient partner datasets  114  in the servers  102 . In an embodiment, patient partners  116 A,  116 B are third parties who have received and recovered from medical device implant surgeries. However, patient partners  116 A,  116 B may be third persons with other forms of first-hand experience with one or more medical concerns. Patient partners  116 A,  116 B provide preoperative patients an opportunity to converse with someone having first-hand experience with their selected medical procedure, surgeon and/or medical implant device. Post-operative patients may become patient partners  116 A,  116 B by electing to join the patient partner program. In many cases, post-operative patients are invited/recommended to join the patient partner program by their surgeon. 
     As illustrated in  FIG. 4B , in an embodiment, the method  300  at block  304  includes obtaining the technical data  106  and/or specifications of one or more medical implant devices from their original equipment manufacturers (OEMs) and surgeon data  112  from the OEM. In an embodiment, the medical implant device technical data  106  and surgeon data  112  is acquired from OEM web pages  104  and/or databases  104  by web data extraction and stored on one or more servers  102  (e.g., a first computer memory). Persons skilled in the relevant arts will recognize that additional methods of data acquisition may be utilized in conjunction with web data extraction, or instead of web data extraction, to obtain the medical implant device technical data  106 . For example, the medical implant device technical data  106  may also be obtained via manual data acquisition. 
     The method  300  continues at block  306  by generating a database of surgeons currently trained to surgically implant a first medical implant device (e.g., a knee arthroplasty implant) and operating within a first geographic region (e.g., the San Diego metropolitan area). The database of surgeons may be generated via the processor  110  as a function of the medical implant device data  106  and the surgeon data  112  obtained at block  304 . However, the database of surgeons may also be generated as a function of medical implant device data  106  and the surgeon data  112  that has previously been downloaded, uploaded, or otherwise transferred to the one or more servers  102 . 
     At block  308 , the method  300  continues by storing the database of surgeons on the servers  102 . The method  300 , at block  310 , includes assigning one or more surgeon-variables to each of the one or more surgeons via the processor  110 , wherein the assignment is stored in the servers  102 . For example, the surgeon-variables may include, but are not limited to, number of years in surgical practice, number of specific medical implant device procedures performed, geographic location, and surgical specialty. In an embodiment, the surgeon-variables are extracted or otherwise generated from the surgeon data  112  obtained at block  304 . Although only one geographic region and one medical implant device type may be referred to with regard to the method  300  for clarity of description, the database of surgeons generated in the method  300  will generally include multiple geographic regions and multiple medical implant device types. Similarly, some surgeons may be assigned to more than one medical implant device in the servers  102 . 
     The method  300  continues at block  312  by storing one or more queries (e.g., questions) assigned to the one or more surgeon-variables at the one or more servers  102 . Assigning one or more queries to the surgeon-variables facilitates filtering the available surgeons into a set of surgeons that meet the requirements of a particular patient. At block  314 , assigning one or more patient partners  116 A,  116 B to the one or more surgeons in the database of surgeons as a function of the patient partner datasets. 
     As illustrated in  FIG. 4B , the method  300  connects a client computer  108 A,  108 B with the servers  102  at block  316 , and transmits one or more queries to the client computer  108 A,  108 B at block  318 . At block  320 , the processor  110  receives one or more data inputs from the client computer  108 A,  108 B in response to the queries. Then at block  322 , generating a list of patient partners  116 A,  116 B as a function of the data input. 
     In an embodiment, at block  324 , the method  300  includes determining whether a data input has been received for each query transmitted at block  318 . If a data input has been received for each query, the method  300  continues at block  326  by transmitting to the client computer  108 A,  108 B the list of patient partners  116 A,  116 B. If a data input has not been received for each query, the method  300  returns to block  318  and transmits one or more queries to the client computer  108 A,  108 B. 
     In an embodiment, as illustrated in  FIGS. 1 and 4C , a method  350 , at block  352 , stores a plurality of patient partner datasets  114  in the servers  102  as in the method  300 . At block  354 , the method  350  assigns patient partner-variables to the patient partners  116 A,  116 B. The method  350  continues at block  356  by storing one or more queries assigned to the one or more patient partner-variables at the one or more servers  102 . At block  358 , the method  350  connects a client computer  108 A,  108 B with the one or more servers  102 . Next, the queries transmitted to the client computer at block  360  include one or more queries assigned to the one or more patient partner-variables and the data inputs received, by the processor, at block  362  include one or more data inputs from the client computer in response to the one or more queries assigned to the one or more patient partner-variables. At block  364 , the method  350  generates a list of patient partners  116 A,  116 B as a function of the data input. 
     The method  350 , at block  366 , includes determining whether a data input has been received for each query transmitted at block  360 . If a data input has been received for each query, the method  350  continues at block  38  by transmitting to the client computer  108 A,  108 B the list of patient partners  116 A,  116 B. If a data input has not been received for each query, the method  350  returns to block  360  and transmits one or more queries to the client computer  108 A,  108 B. 
     In an embodiment, at block  318 ,  360  the queries may be transmitted to the client computer  108 A,  108 B in a sequential manner. In such an embodiment, the queries earlier in the sequence may be directed to evoking data input which enables the filtering of surgeons in the database of surgeons. For example, initial queries may prompt data input concerning, for example, the type of surgery in question and the geographic location of the preoperative patient. At block  322  the method  300  continues by generating a list of surgeons as a function of the one or more data inputs via the processor  110 . Following queries may then be directed to prompt data input concerning, for example, the pre-operative patient&#39;s surgical experience, preferred gender of a patient partner, the pre-operative patient&#39;s age, and the pre-operative patient&#39;s activity level. Then generating a list of patient partners  116 A,  1166  as a function of the list of surgeons and data input. 
     In an embodiment, as illustrated in  FIG. 5 , the methods  300 ,  350  include an integrated user feedback component utilized to update the list of patient partners  116 A,  116 B stored on the servers  102 . For example, at block  370  the server  102  may store two or more numerical values assigned to two or more levels of patient satisfaction. After a predetermined period of time, and/or after receiving input from a patient that their surgical procedure has been completed, at block  372  the processor  110  may transmit a query to the client computer  108 A,  108 B comprising a multiple choice answer in the form of two or more levels of satisfaction with their patient partner  116 A,  116 B. At block  374 , upon receiving the data input corresponding to the patient&#39;s level of satisfaction, the processor  110  amends a patient partner-variable value corresponding to the patient partner&#39;s ranking at block  376 . As a result, patient partners  116 A,  116 B in a list generated at block  326 ,  368  may be listed in order of patient satisfaction (i.e., ranking) at block  378 . 
     As illustrated in  FIGS. 1 and 6 , in an embodiment, the servers  102  and processor  110  are in direct or indirect signal communication with the client computers  108 A,  1086 , the OEM web pages  104  and/or databases  104 , and the patient partners  116 A,  1166  via the communication network  118 . Exemplary embodiments of servers  102  are also able to manipulate, manage, transmit, receive, and edit data files maintained within its memory or located on its hard disk. Exemplary embodiments of the communication network  118  include a LAN, WAN (e.g., the internet), public networks, and private networks. 
     One or more features of the embodiments described herein may be combined to create additional embodiments which are not depicted. While various embodiments have been described in detail above, it should be understood that they have been presented by way of example, and not limitation. It will be apparent to persons skilled in the relevant arts that the disclosed subject matter may be embodied in other specific forms, variations, and modifications without departing from the scope, spirit, or essential characteristics thereof. The embodiments described above are therefore to be considered in all respects as illustrative, and not restrictive. The scope of the invention is indicated by the appended claims, and all changes that come within the meaning and range of equivalents thereof are intended to be embraced therein.