Systems and methods for compliance related analytics

Abstract

Aspects of the technology provide a system architecture for evaluating therapy device usage data received from a plurality of remote therapy devices. The system (100) may be implemented with one or more databases. The databases may contain a plurality of archived data parameters concerning data received from the plurality of remote therapy devices. The one or more servers may include a plurality of services. Each service may be configured to receive requests relating to a predefined data subset of the plurality of data parameters, and to transmit, to a remote client device, a report including data of the predefined data subset and one or more performance indicators. Each of the plurality of services may be further configured to evaluate the predefined data subset based on the requests to generate the one or more performance indicators, which may concern usage compliance of the therapy devices.

Description

SYSTEMS AND METHODS FOR COMPLIANCE RELATED ANALYTICS1 CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of United States Provisional Patent Application No. 63 / 519,973, filed August 16, 2023, the entire content of which is incorporated herein by reference.2 BACKGROUND OF THE TECHNOLOGY2.1 FIELD OF THE TECHNOLOGY

[0002] The present technology relates to systems for providing data and analytics related to therapy devices such as usage and / or compliance requirements. In particular, the present technology relates to architecture of systems for monitoring performance associated with home medical equipment (HME), such as using a compliance-based performance evaluation2.2 DESCRIPTION OF THE RELATED ART

[0003] Many people require the use of therapy devices, such as on a daily basis. For example, it is believed that more than 8 million positive airway pressure (e.g., CPAP) devices are sold annually in the United States, with another 2.5 million globally. When using an HME device, a patient may need to continuously comply with a certain compliance, therapy or device usage requirement or standard in order to receive the maximum benefit provided by the HME device.

[0004] Patient compliance with compliance requirements may benefit a HME provider who provides the HME device to the patient(s). Thus, thousands of HME providers, which may each manage hundreds of patients, may have systems and / or personnel to assist, such as with instruction and coaching, the patient on how to use the HME device. The HME provider may be eligible to receive a reimbursement from the patient’s insurer (e.g., insurance company) when the patient uses the HME device pursuant to his / her compliance requirement. An example compliance requirement may be a standard provided by Centers for Medicare & Medicaid Services (CMS) or a standard provided by the Medica Medicare Medicaid, which, for example, may require the patient to use a respiratory therapy type HME device for at least four hours for 21 out of 30 days in a 90-day window period, in order for the HME provider to receive the reimbursement. Furthermore, a patient who continuously meets the compliance requirement may be a candidate for frequent resupply of HME device accessories such as masks and tubes.

[0005] As a result, the HME providers are incentivized to have systems and / or clinicians for motivating the patients on using the HME device to meet the compliance requirement. Some HME providers have systems / clinicians in different locations that provide coaching services to the patients.

[0006] Existing technologies merely assess compliance of individual patients, but do not provide broader benchmark assessments, such as for HME providers with respect to their performance, such as in relation to coaching and / or assisting their patients to remain compliant. Typical prior technologies do not provide for practical access to, or analysis of such data, let alone sufficient data, nor can such data be readily evaluated or understood to provide such benchmark assessments since such information is generally widely dispersed and not well suited to tracking and evaluation, such as when vast amounts of data is necessary for benchmarking assessments. The present technology, such as in relation to therapy device communications and data compilation systems with electronic communication systems (e.g., networked HME devices and server-based database(s)), improves data analytics processing and / or systematic computation analysis with computational machines (i.e., computers) so as to provide technological improvement that overcome the shortfalls of existing systems.

[0007] For each HME provider, there is a need to understand performance of its systems / clinicians and locations, as well as performance benchmarks in the industry, which may help the HME provider make improved decisions with respect to taking suitable actions to improve its performance, which in turn may improve patient health as a collective.3 BRIEF SUMMARY OF THE TECHNOLOGY

[0008] The present technology is directed towards a system for monitoring performance of HME providers, clinicians, physicians or insurers, measured by their patients’ compliance success when using HME devices.

[0009] Some implementations of the present technology may include a system architecture for evaluating therapy device usage data received from a plurality of remote therapy devices. The system may include one or more servers including one or more databases. The databases may contain a plurality of archived data parameters. The plurality of archived data parameters may concern data received from the plurality of remote therapy devices. The one or more servers may further include one or more services. Each of the one or more services may be configured to receive one or more requests, or electronic requests, relating to a respectivepredefined data subset of the plurality of archived data parameters, and may also be configured to transmit, and / or generate for transmission, to a remote client device, a report, or electronic report, including data of the respective predefined data subset and one or more performance indicators characterizing one or more associations of data of the respective predefined data subset. Each of the one or more services may be further configured to evaluate the respective predefined data subset based on the one or more requests to generate the one or more performance indicators based on the evaluation of the respective predefined data subset.

[0010] In some implementations, each of the one or more services may be configured to receive the one or more requests relating to a respective predefined data subset of the plurality of archived data parameters, via a network interface. Each of the one or more services of the one or more servers may be configured to receive one or more requests relating to the respective predefined data subset of the plurality of archived data parameters, and to transmit, to an internal device, a report including data of the respective predefined data subset and one or more performance indicators characterizing one or more associations of data of the respective predefined data subset. The one or more requests may include a filter criterion. The filter criterion may include one or more of: a location identifier; a clinician or physician identifier; a model identifier for a remote therapy device; a model identifier for a component used with a remote therapy device; a usage period; an insurer identifier; data indicating initial setup of a remote therapy device; and a compliance rule for usage of a remote therapy device. Each service of the one or more services may be configured to produce reports in a plurality of formats. The plurality of formats may include one or more of: i) email, ii) file transfer, iii) stream, or iv) secure graphic user interface rendering of information. The one or more performance indicators may include one or more benchmarks. One or more remote therapy devices of the plurality of remote therapy devices may be a respiratory therapy device(s). One or more remote therapy devices of the plurality of remote therapy devices may be a positive airway pressure therapy device(s).

[0011] Some implementations of the present technology may include a method for evaluating therapy device usage data received from a plurality of remote therapy devices. The method may include receiving, data from the plurality of remote therapy devices, the data containing a plurality of data parameters. The method may include archiving, at one or more servers that may include one or more databases, the data including the plurality of data parameters, which may be into the one or more databases. The method may include receiving requests from a plurality of remote client devices. The requests may relate to a predefined datasubset of the plurality of data parameters. The method may include evaluating, by a service of a plurality of services of the one or more servers, data of the predefined data subset. The method may include generating, by the service of the plurality of services of the one or more servers, one or more performance indicators characterizing one or more associations of the data of the predefined data subset. The one or more performance indicators may be based on the evaluation of the predefined data subset. The method may include generating for transmission and / or transmitting, in response to a request of the requests, a report including the data of the predefined data subset and the one or more performance indicators to a remote client device of the remote client devices.

[0012] In some implementations, the method may further include receiving, by the service of the plurality of services of the one or more servers, requests from one or more internal devices. Such requests may relate to a predefined data subset of the plurality of data parameters. The requests may relate to a predefined data subset of the plurality of data parameters includes one or more filter criterions. A filter criterion of the one or more filter criterions may include one or more of: a location identifier; a clinician or physician identifier; a model identifier for a remote therapy device; a model identifier for a component used with a remote therapy device; a usage period; an insurer identifier; data indicating initial setup of a remote therapy device; and a compliance rule for usage of a remote therapy device. The method may further include transmitting, via a network interface, the requests from the remote client devices to the service of the plurality of services. The method may further include producing, by the service of the plurality of services, the report in a plurality of formats. The plurality of formats may include one or more of: i) email, ii) direct file transfer, iii) stream, and iv) secure graphic user interface rendering of information. The one or more performance indicators may include one or more benchmarks. The plurality of remote therapy devices may include respiratory therapy devices. The plurality of therapy devices may include positive airway pressure therapy devices. The receiving the requests from remote client devices may be received via a network interface.

[0013] Some implementations of the present technology may include a processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method of evaluating therapy device usage data received from a plurality of remote therapy devices with to any one or more of the aspects of the methods described herein.

[0014] Some implementations of the present technology may include a processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors, such as one or more servers, to perform a method of evaluating therapy device usage data received from a plurality of remote therapy devices. The processor-executable instructions may include instructions to receive, data from the plurality of remote therapy devices, the data containing a plurality of data parameters. The processor-executable instructions may include instructions to archive, at one or more servers including one or more databases, the data including the plurality of data parameters into the one or more databases. The processor-executable instructions may include instructions to receive requests from a plurality of remote client devices, the requests relating to a predefined data subset of the plurality of data parameters. The processor-executable instructions may include instructions to evaluate, by a service of a plurality of services of the one or more servers, data of the predefined data subset. The processor-executable instructions may include instructions to generate, by the service of the plurality of services of the one or more servers, one or more performance indicators characterizing one or more associations of the data of the predefined data subset, wherein the one or more performance indicators may be based on the evaluation of the predefined data subset. The processor-executable instructions may include instructions to transmit, in response to a request of the requests, a report including the data of the predefined data subset and the one or more performance indicators to a remote client device of the remote client devices.

[0015] Of course, portions of the aspects may form sub-aspects of the present technology.Also, various ones of the sub-aspects and / or aspects may be combined in various manners and also constitute additional aspects or sub-aspects of the present technology.

[0016] Other features of the technology will be apparent from consideration of the information contained in the following detailed description, abstract, drawings and claims.4 BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present technology is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings, in which like reference numerals refer to similar elements including:

[0018] FIG. 1 illustrates an environment in which a system monitors performance associated with HME, according to one aspect of the present invention.

[0019] FIG. 2 illustrates another environment in which a system monitors performance associated with HME, according to one aspect of the present invention.

[0020] FIG. 3 illustrates an example flow chart of a method for monitoring performance associated with HME, according to one aspect of the present technology.

[0021] FIG. 4 illustrates another example flow chart of a method for monitoring performance associated with HME, according to one aspect of the present technology.

[0022] FIG. 5 illustrates yet another example flow chart of a method for monitoring performance associated with HME, according to one aspect of the present technology.

[0023] FIGs. 6 and 6B illustrate example system architectures in accordance with aspects of the disclosure.

[0024] FIG. 7 illustrates and example method in accordance with aspects of the disclosure.

[0025] FIG. 8 A shows a system including a patient 1000 wearing a patient interface 3000, in the form of nasal pillows, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device 4000 is humidified in a humidifier 5000, and passes along an air circuit 4170 to the patient 1000. A bed partner 1100 is also shown. The patient is sleeping in a supine sleeping position.

[0026] FIG. 8B shows a system including a patient 1000 wearing a patient interface 3000, in the form of a nasal mask, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device is humidified in a humidifier 5000, and passes along an air circuit 4170 to the patient 1000.

[0027] FIG. 8C shows a system including a patient 1000 wearing a patient interface 3000, in the form of a full-face mask, receiving a supply of air at positive pressure from an RPT device 4000. Air from the RPT device is humidified in a humidifier 5000, and passes along an air circuit 4170 to the patient 1000. The patient is sleeping in a side sleeping position.

[0028] FIG. 9A shows an RPT device in accordance with one form of the present technology.

[0029] FIG. 9B is a schematic diagram of the pneumatic path of an RPT device in accordance with one form of the present technology. The directions of upstream and downstream are indicated with reference to the blower and the patient interface. The blower is defined to be upstream of the patient interface and the patient interface is defined to be downstream of the blower, regardless of the actual flow direction at any particular moment. Items which are located within the pneumatic path between the blower and the patient interface are downstream of the blower and upstream of the patient interface.

[0030] FIG. 9C is a schematic diagram of the electrical components of an RPT device in accordance with one form of the present technology.

[0031] FIG. 9D is a schematic diagram of the algorithms implemented in an RPT device in accordance with one form of the present technology.5 DETAILED DESCRIPTION OF EXAMPLES OF THE TECHNOLOGY

[0032] Before the present technology is described in further detail, it is to be understood that the technology is not limited to the particular examples described herein, which may vary. It is also to be understood that the terminology used in this disclosure is for the purpose of describing only the particular examples discussed herein, and is not intended to be limiting.

[0033] The following description is provided in relation to various examples which may share one or more common characteristics and / or features. It is to be understood that one or more features of any one example may be combinable with one or more features of another example or other examples. In addition, any single feature or combination of features in any of the examples may constitute a further example.5.1 MONITORING SYSTEM

[0034] FIG. 1 illustrates an environment in which an example system 100 monitors performance associated with HME. As shown in FIG. 1, an HME provider 110 may provide one or more HME devices 112a-f to one or more patients 114a-f, and hire one or more clinicians 116a-c to coach the patients 114a-f on how to use the HME devices 112a-f to meet a compliance, adherence, or therapy requirement. Each HME device may be a respiratory treatment (RPT) device, details of which are discussed in section 4.2. The system 100 may store, such as in a memory described herein, a first receipt date of a therapy device as well as device usage information according to each day of use such as to report whether or not a patient met compliance within a certain time window, such as within 30 days of first receiving a device, or longer, such as within 31 to 90 days, as well as whether patients were not compliant such as within these windows. Such usage data can be evaluated by the system to determine each patient’s time (e.g., number of days) to first satisfying a compliance requirement from first receiving a therapy device. As such, the compliance requirement may be a device usage requirement, which indicates a predetermined number of device operation hours. Thus, the predetermined number of device hours may represent an expected amount of time that a patient should use an HME device within a predetermined period of time. In one example, the device usage requirement may require the patient to use the HME device for at least four hours for 21 out of 30 days in a 90-day window period. For each patient who meets the device usagerequirement, the HME provider may get a reimbursement from the patient’s insurer (e.g., insurance company).

[0035] The HME provider 110 may provide coaching services to the patients at different geographic locations 118a and 118b. The geographic location 118a or 118b may refer to a country, state, province or city, among other possibilities. It one example, the HME provider 100 may coach patients 114a-f in Florida, Texas, and North Carolina.

[0036] The HME provider 110 may partner with one or more physicians 120a-c. Each patient may receive coaching not only from a clinician of the HME provider 110, but also optionally from a physician. The relationship between a patient and his / her clinician and / or physician may impact the patient’s compliance to the compliance requirement. If a clinician / physician has a better relationship with the patient, the patient may be more likely to meet the compliance requirement. When a patient receives coaching from both the clinician and the physician, the patient may have an increased chance to comply with the compliance requirement.

[0037] The system 100 may monitor performance of one or more HME providers 110, one or more clinicians 112a, 112b and 112c, one or more locations 118a and 118b where the clinicians provide coaching to the patients, one or more physicians 120a, 120b and 120c who also provide coaching to the patients regarding use of the HME devices, and one or more insurers who provide insurance to the patients. The system 100 may measure each performance based on a percentage or a number of patients who comply with the compliance requirement.

[0038] The system 100 may include one or more processors 102, memory 104, and a network interface 106. The system 100 may have one or more services, such as application programming interface(s) (API), which may be integrated with other systems for access to the system 100. The system may be implemented according to an architecture as described in more detail herein.

[0039] The processor(s) 102 may be a dedicated electronic circuit or an applicationspecific integrated circuit. The processor 102 may be formed with discrete electronic components. The processor 102 may include a dedicated motor control integrated circuit. The processor 102 may include one or more processors or microprocessors, configured to execute one or more computer programs stored in the memory 104.

[0040] The memory 104 may be a non-transitory computer-readable medium configured to store one or more algorithms and / or methods described herein in the form of computer program instructions. The memory 104 may include one or more of the following: non-volatilememory, batery powered static random-access memory (RAM), and volatile RAM. The memory 104 may be in the form of electrically erasable programmable read-only memory (EEPROM) or NAND flash. The memory 104 may be implemented with one or more databases.

[0041] The memory 104, such when implemented as one or more database(s), may store mapping relationships of one or more of the following: HME provider(s), clinician(s), patient(s), physician(s), location(s), insurer(s) and HME device(s), each of which may have a unique identifier. For instance, each patient may have a unique patient identifier. Each clinician and physician may have a unique coach identifier. Alternatively, each clinician may have a unique clinician identifier, and each physician may have a unique physician identifier. Each insurer may have a unique insurer identifier. Each HME device may have a unique HME device identifier. For each HME provider, the memory 104 may store mapping relationships indicating which patients, clinicians, physicians and insures are associated with the HME provider. For each patient, the memory may store mapping relationships indicating which HME provider, clinician and insurer serve the patient. If the patient has a physician, the memory may also store a mapping relationship reflecting association between the patient and the physician. For each physician, the memory may store mapping relationships indicating which HME provider and patients are associated with the physician. For each insurer, the memory may store mapping relationships indicating which HME providers, patients, and physicians are associated with the insurer.

[0042] The memory 104 may store information for each patient, such as the aforementioned usage information. The memory may store other information for each patient including, for example, whether or not the patient has activated a companion device (e.g., tablet, smart phone, etc.) with an application (e.g., a downloaded app) configured for communicating therapy device related information to the patient such as from the system 100 and / or with the patient’s therapy device. In some implementations, the memory may also store one or more of the following information for each patient: (1) at least one coach identifier identifying at least one coach who coaches the patient, and (2) a geographic location where the patient receives coaching from the at least one coach. The at least one coach of each patient may include a clinician and / or a physician.

[0043] In some implementations, the memory 104 may store one or more of the following information for each patient: (1) an HME provider identifier identifying one of the plurality of HME providers associated with the patient, (2) a physician identifier identifying a physicianwho coaches the patient on using the HME device; (3) a geographic location where the patient receives coaching for using the HME device; and (4) an insurer identifier identifying an insurer associated with the patient as well as the other information described herein.

[0044] To illustrate some implementations, for a system 100 that provides intraorganization performance indicators as shown in FIG. 1, the memory 104 may store information associated with each patient, including one or more of the following: at least one coach identifier identifying a coach who coaches the patient, a geographic location where the patient receives coaching from, a patient identifier that identifies the patient, an HME device identifier that identifies the HME device used by the patient, and an insurer identifier that identifies an insurer who provides insurance to the patient. A patient may have one or two coaches, such as a clinician and / or a physician. The coach identifier may include a clinician identifier and / or a physician identifier. In addition, the memory 104 may store information associated with each clinician, including one or more of the following: a coach identifier or a clinician identifier that identifies each clinician, and one or more geographic locations where each clinician provides coaching. The memory 104 may also store information associated with each physician, including one or more of the following: a coach identifier or a physician identifier that identifies the physician, one or more geographic locations where the physician provides coaching, and one or more insurer identifiers that identify insurer(s) who partner with the physician.

[0045] To illustrate some implementations, for a system 100 that provides industry performance indicators as shown in FIG. 2, the memory 104 may store the following additional information, reflecting patient, clinician and physician relationships with respect to HME providers. For each HME provider, the memory 104 may store an HME provider identifier, one or more associated clinician identifiers identifying clinician(s) who work for the HME provider, one or more associated physician identifiers identifying physician(s) who work for the HME provider, and one or more associated patient identifiers identifying patient(s) who receive coaching from the HME provider, and one or more associated insurer identifiers identifying insurer(s) who partner with the HME provider. In addition, with respect to each patient, the memory 104 may store an HME provider identifier that identifies the HME provider associated with the patient. Similarly, with respect to each clinician and each physician, the memory 104 may store an HME provider identifier that identifies the HME provider associated with the clinician and the physician.

[0046] The network interface 106 may communicate with one or more HME devices 112a- f and one or more remote devices 130 by using a wired or wireless communication interface. The wired communication interface 1008 may include a wired protocol, to allow, for example, communication to the Internet via Ethernet or optical fibre. The wireless communication interface may include one or more transceivers using wireless protocols such as infrared protocol, cellular, Bluetooth, WIFI, Bluetooth LE, and Bluetooth BLE (5.0) with GATT profile, among other possibilities.

[0047] In one example, each HME device may report device usage, along with the HME device identifier, to the processor 102 via the network interface 106. Based on such information, the processor 102 may identify patients who meet or adhere to the compliance requirement.

[0048] The processor 102 may determine whether each patient is a compliant patient by comparing the device usage of each patient to the device usage requirement. The processor 102 may also determine for one or more, such as a chosen group of patients, such as in response to a filter criterion, an average time to compliance, a minimum time to compliance, a median time to compliance or a maximum time to compliance.

[0049] The processor 102 may generate one or more performance indicators 132 for output to a user. The user may include, but not limited to, clinician(s), decision maker(s) within HME provider(s) 110, such as manager(s) of the clinician(s), physician(s) and insurer(s), among other possibilities. Users at different hierarchical levels within the HME provider 110 may have access to different information. In one example, the system 100 may be accessed by a clinician or his / her manager to view the clinician’s performance over a period of time, e.g., over the last few months.

[0050] The processor 102 may receive a filter criterion 134 from the user. The filter criterion 134 may concern information stored in the memory 104. In one example, the filter criterion may include at least one selected coach identifier and / or at least one selected geographic location. The at least one selected coach identifier may identify at least one clinician and / or at least one physician. In another example, the filter criterion may include one or more of the following: at least one selected HME provider identifier, at least one selected physician identifier, at least one selected geographic location, and at least one selected insurer identifier. In turn, the processor 102 may generate a performance indicator, for output to the user, which may be based on, for example, a number of compliant patients or non-compliant patients, or other compliance related information, such as a time to compliance, average time tocompliance, median time to compliance, minimum time to compliance, maximum time to compliance, etc., whose information meets the filter criterion.

[0051] In one example, the user may access the system 100 via the remote device 130. The remote device 130 may be a mobile phone, tablet, laptop, personal computer, or other computing or computer device. The remote device 130 may communicate wirelessly with the system 100.

[0052] The user may submit the filter criterion 134 from the remote device 130 to the system 100. The filter criterion may include a single filter or an aggregated filter. In one example, a single filter may select a single physician or a single location. In one example, the aggregated filter may select one or more physicians and / or locations.

[0053] After receiving the filter criterion 134, the system 100 may generate the performance indicator 132 for output to the user and / or other analytical data associated with the filter criterion. The system may display the performance indicator 132 and / or the other analytical data associated with the filter criterion, in an easy way for the user to sift through.

[0054] The performance indicator 132 may include an aggregated performance report and / or insight. For example, the performance indicator may provide one or more performance benchmarks to the user, help the user identify any performance decrease, and where, how and when the performance decrease occurs. Various examples of performance benchmarks generated by the system 100 are described below.

[0055] The system 100 may be implemented with a particular architecture, such as with discrete data sets and one or more dedicated services for each, such as for automating a production and access to the information of the dataset that is responsive to a filter criterion. Thus, such a dataset may be based on the information of the memory, and the data thereof may optionally be anonymised such as to remove patient identity, clinician identity, physician identity information, for example, while keeping generalized information regarding such individuals / entities for the reporting / insight generation as described herein.

[0056] An example architecture for such a system is illustrated in Figs. 6A and 6B. For example, FIGs. 6A-6B illustrate example architectures of a system 800a, 800b. System 800a, 800b may be implemented with aspects of the system 100 discussed above, such as with the memory 104 and processor(s) 102 previously described. System 800a, 800b may include one or more servers 802. The one or servers 802 may include one or more databases 804, such as with the aforementioned memory 104, a plurality of services 806, one or more network interfaces 808.

[0057] The one or more databases 804 of one or more servers 802 may be configured with the memory 104 to store archived data such as related to the one or more remote medical devices as previously described. Thus, the archived data may include a plurality of data parameters (e.g., values stored). The plurality of data parameters may include compliance data associated with the one or more remote medical devices. The plurality of data parameters may additionally include values such as location (e.g., clinician organization office, geographic, region, etc.), associated physician and / or lack of associated physician,), device model, insurer, date and time a device was initialized or first setup, whether or not the patient has activated a companion device. Additionally or alternatively, the plurality of data parameters of the archived data may include any other values collected or determined by the one or more remote medical devices.

[0058] Each service 806 may be configured to access / generate a pre-determined subset of data of the database(s) of the server such as to generate particular analytic information concerning the pre-determined subset of data. One such dataset may comprise a plurality of data parameters forming the compliance related performance indicator(s) as described in more detail herein. Other datasets may be different or overlap with such a dataset and provide different output concerning the service 806 that is associated with the particular dataset. As such, the service 806 (e.g., an API) may be configured to repeatedly produce / generate a similar report concerning performance information as described herein and may be configurable to produce such a report in a selectable format (e.g., to a graphic user interface, by email, by file transfer to a remote server location (e.g., folder location or database upload) stream, or other secure rendering of information) at a selectable period (e.g., weekly, monthly, bi-monthly etc.) and / or on demand. For example, a user can access the API associated with a particular dataset, such as with the performance indicators herein, to configure the system via the API to produce, from the dataset, an automatic monthly delivery of pre-selected performance indicator(s). As such the performance indicators will be updated with new database data and repeatedly delivered to the user on, for example, a monthly basis.

[0059] Optionally, one or more network interfaces 808 may be implemented and may communicate with each service 806 or all of such services. The one or more network interfaces 808 may be configured to respond to one or more requests from a remote client device(s) and serve as an intermediary for communications to and from the service(s) 806. Optionally, the one or more network interfaces may be one network interface. In this regard, the one network interface may be configured to communicate information to and from the one or more servers802 of system 800a, via the service(s). For example, the one or more network interfaces 808 may be configured to transmit one or more requests to each of the plurality services 806. Such an interface 808 may provide communication management services for managing requests to the services.

[0060] Thus, the one or more requests may relate to a particular service concerning a predefined data subset of the plurality of data parameters of the database. By way of example, the predefined data subset or dataset of the database(s) described herein may be limited to include data associated with any filter combination of criterion of the data parameters as previously described. For example, the one or more requests may be filter criterion 134 and the predefined data subset or dataset may include data associated with the data parameters of the criterion. In such an example the criterion may be at least one selected coach identifier and / or at least one selected geographic location, discussed above and the data of the dataset would include the data responsive to such a filer criterion.

[0061] Accordingly, each service 806 may include one or more programs such as with an application programming interface for evaluating data based on the one or more requests. In this regard, the plurality of services may be configured to generate and / or deliver a report of one or more performance indicators of a dataset. As such, the one or more performance indicators may characterize one or more associations of the data of the predefined data subset or dataset corresponding to a request. Moreover, the one or more performance indicators may be utilized to form a report, or performance report. As such, the report may include the data of the predefined data subset corresponding to a request, the criterion of the request and the one or more performance indicators. The report may be indicative of one or more performance benchmarks (e.g., performance benchmarks discussed below in 4.1.1).

[0062] For example, a request may include criterion of a particular location or a particular physician. In such an example, the archived data pertaining to therapy devices associated with the particular location may be processed in a service directed towards location related dataset and another service directed towards a physician related dataset. In this regard, the service directed towards location may generate one or more performance indicators relating to the particular location, and the service directed towards physician may generate one or more performance indicators relating to the particular physician. The one or more performance indicators may include values determined based on the data associated with particular criterion of the request. For example, the one or more performance indicators may include number of compliant patients, number of non-compliant patients, average time to compliance, minimumtime to compliance, median time to compliance, maximum time to compliance, minimum time of non-compliance, average time of non-compliance, maximum time of non-compliance, median time of non-compliance, total number of medical devices activated, number of companion device applications activated and / or not activated, etc. Additionally or alternatively, in such an example, a service of the plurality of services may be directed towards both location and physician and be configured to generate one or more performance indicators relating to both the particular physician and the particular location.

[0063] As previously discussed, the one or more remote medical devices may be HME devices such as HME devices (e.g., HME devices 112a-l, RPT device 4000, etc.). The data from the one or more remote medical devices may optionally be received via the one or more network interfaces 808 or other network services.

[0064] Additionally, or alternatively, as illustrated in FIG. 6B, one or more internal device(s) 812 may be included in system 800b. In this regard, the internal device(s) 812 may be similarly configured to send requests to the one or more services 806 of the one or more servers 802 and receive reports as with the remote client devices but may be configured to do so without use of the one or more network interfaces 806.5.1.1 Example Performance Benchmarks5.1.1.1 Intra-organizational Performance Benchmarks

[0065] In one example, referring to FIG. 1, the system 100 may provide benchmarks for use within a HME provider 110 to identify systemic issues within the HME provider. In this example, users of the system 100 may be limited to people who work inside the HME provider 110, including for example clinicians and / or managers of clinicians within the HME provider 110.5.1.1.1.1 Clinician Performance

[0066] The system 100 may determine performance of one or more clinicians hired by the HME provider 110. In one example, each clinician’s performance may depend on a number or a percentage of compliant patients coached by the clinician relative to the total number of patients coached by the clinician. In some implementations, the greater number of compliant patients that a clinician coaches, the better the clinician’s performance.

[0067] The system 100 may track each clinician's performance over time. For instance, the system 100 may track each clinician’s average performance per month. The performance indicator 132 generated by the system 100 may indicate a progression of the number of compliant patients coached by each clinician over time. When the clinician’s performancedrops below his / her average performance, the system 100 may generate a message. For example, if a clinician on average coaches about 50 compliant patients a month, the system 100 may generate a message when the clinician’s performance drops to 30 compliant patients a month. The message may be sent to the clinician and / or the clinician’s manager.

[0068] In one example, the system 100 may process a filter criterion that identifies a clinician working within the HME provider. The system 100 may output a performance indicator of the identified clinician. The performance indicator may indicate a comparison between performance of the identified clinician and an acceptable threshold. The acceptable threshold may be an average number of compliant patients per coach as determined by the system 100. The performance indicator may indicate a comparison between the number of compliant patients, coached by the clinician and the acceptable threshold. When the number of compliant patients, coached by the clinician, falls below the acceptable threshold, the processor may generate a message. In one example, the processor may send the generated message to the clinician or the clinician’s manager.

[0069] Sometimes a clinician may work at multiple locations. When the system 100 receives an aggregated filter identifying a particular clinician at a particular location, the system 100 may generate a performance indicator for that particular clinician at that particular location.

[0070] In another example, the system 100 may process a filter criterion that identifies two or more clinicians working for the same HME provider. The system 100 may output a performance comparison between these identified clinicians. Such comparison may help managers or decisionmakers within the HME provider understand deviations in clinicians’ performance. If one clinician has a better performance than another clinician, they may share expertise to improve overall performance.

[0071] In one example, the performance indicator may include an average number of patients per coach.5.1.1.1.2 HME Provider Performance

[0072] In one example, the system 100 may generate a performance indicator indicating an average number of compliant patients coached by the HME provider on a monthly basis. For example, the system 100 may track performance of each clinician of the HME provider over a period of time, and determine an average number of compliant patients coached by all clinicians of the HME provider per month. Based on how many patients its clinicians can coach, the HME provider may make hiring decisions or adjust workloads.

[0073] In one example, the system 100 may output a performance indicator 132 indicating a ratio between a total number of compliant patients and a total number of patients served by the HME provider 110. For instance, the performance indicator 132 may indicate that the HME provider has about 60% compliant patients, meaning that 60% of overall patients served by the HME provider are compliant to the compliance requirement.5.1.1.1.3 Location Performance

[0074] The system 100 may benchmark location performance. A location can be, for example, a specific address or more generally, a state, a town, a region (e.g., a north eastern region such as one comprising a plurality of states or a plurality of towns, etc.), or a plurality thereof. For example, the system 100 may compare performance of difference geographic locations where clinicians of the HME provider coach patients. In one example, each location’s performance may depend on a number or a percentage of compliant patients coached at that location relative to the total number of patients coached at that location. In one example, the greater the number of compliant patients in a location, the better the performance of that location.

[0075] In one example, the system 100 may process a filter criterion 134 that identifies one location. The system 100 may output a performance indicator indicating a number of compliant patients coached at the identified location.

[0076] In another example, the system 100 may process a filter criterion 134 that identifies two locations, such as Florida and Texas. The system 100 may output a performance comparison between these locations. For example, the system 100 may output a performance indicator including: a ratio between a number of compliant patients and a total number of patients coached at a first location, and a ratio between a number of compliant patients and a total number of patients coached at a second location. If one location has a better performance than the other, they may share expertise to improve overall performance.

[0077] In yet another example, the system 100 may process a filter criterion 134 that identifies a clinician at a particular location (e.g., a particular office address). The system 100 may output a performance indicator indicating a number of compliant patients coached by the identified clinician at the particular location.5.1.1.1.4 Physician Performance

[0078] The system 100 may benchmark physician performance. In one example, each physician’s performance may depend on a number or a percentage of compliant patients coached by the physician relative to the total number of patients coached by the patient.Physician performance may correlate to the physician’s communication efficiency with a patient.

[0079] In one example, the system 100 may process a filter criterion 134 that identifies two or more physicians. The system 100 may compare performance or compliance results of these physicians.

[0080] In another example, the system 100 may process a filter criterion 134 searching for a top physician (e.g., a physician who provides the best coaching service to patients) in a particular location. The system 100 may output information such as which physician has the highest performance in the particular location.5.1.1.2 Industry Performance Benchmarks

[0081] The benchmarks generated by the system 110 may not be limited to a single HME provider. In one example, with reference to FIG. 2, the system 110 may generate one or more benchmarks for the HME industry. For illustrative purposes, FIG. 2 shows HME providers 110a and 110b which hire clinicians 116a-e to provide coaching services to patients 114a-l regarding HME devices 112a-l in locations 118a and 118b. Some patients may work with insurer 122a, while other patients may work with insurer 122b. Here, the HME devices are provided to the patients by the plurality of HME providers 110a and 110b. In this example, users of the system 110 may include decisionmakers of the HME providers, physicians, and insurers, among other possibilities.

[0082] The system 100 may benchmark HME providers of similar patient volumes or at same geographic locations, so as to provide a competitive lens into the HME industry. Various benchmark examples are provided below.5.1.1.2.1 HME Provider Performance

[0083] In some implementations, the system 100 may receive a filter criterion 134 that identifies two or more HME providers. The system 100 may output a performance comparison between the identified HME providers. In one example, performance of each HME provider may depend on a number or a percentage of compliant patients coached by the HME provider relative to the total number of patients coached by the HME provider.

[0084] The HME providers may have various sizes or have different patient volumes, ranging from small mom and pop shops to large organizations.

[0085] In one example, the system 100 may process a filter criterion 134 that identifies a patient volume. The system 100 may output an average compliance rate of HME providers ofthe identified patient volume. For example, the system 100 may generate an average compliance rate, e.g., 70%, of HME providers having 5000 patients.

[0086] In another example, the system 100 may process a filter criterion 134 that identifies a particular HME provider. In one instance, the performance indicator generated by the system 100 may indicate the number of compliant patients associated with the particular HME provider. In another instance, the system 100 may show a comparison of compliance rates between the identified HME provider and HME providers of a similar patient volume. For instance, the system 100 may generate a compliance rate of the identified HME provider in comparison to an average compliance rate of HME providers of a similar patient volume. The performance indicator generated by the system 100 may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the identified HME provider and (2) an average ratio between a number of compliant patients and a total number of patients per HME provider of a patient volume similar to the identified HME provider identified. In some implementations, the processor may generate a message when the ratio associated with the identified HME provider falls below the average ratio. The processor may send the message to the identified HME provider.

[0087] In one example, the system 100 may show that the identified HME provider of 5000 patients has a compliance rate of 56%, whereas the benchmark for an average HME provider of a similar patient volume is 65%. As such, the identified HME provider performs below the industry average, suggesting a need for improvement within the identified HME provider.

[0088] In one example, the system 100 may process a filter criterion 134 that identifies two or more HME providers of a similar patient volume. The system 100 may output a performance comparison of the identified HME providers. For instance, when comparing two HME providers identified by two HME provider identifiers, the performance indicator generated by the system 100 may include: a ratio between a number of compliant patients and a total number of patients associated with a first HME provider identifier; and a ratio between a number of compliant patients and a total number of patients associated with a second HME provider identifier.

[0089] In one example, the system 100 may process a filter criterion 134 searching for the top HME provider with the highest performance. The system 100 may output which HME provider has the highest compliance rate.

[0090] Performance or compliance results of HME providers may be accessible by physicians and insurers. Based on such information, a physician may choose which HME provider to partner with. Two different patients 114c and 114e may work with the same physician 120b, but with two different HME providers 110a and 110b. The system 100 may process a filter criterion 134 submitted by the physician 120b which identifies these HME providers 110a and 110b. The system 100 may output a performance comparison of the two HME providers 110a and 110b to the physician 120b. The HME provider with a higher performance may have a greater level of patient compliance success. Based on the performance of the HME providers 110a and 110b, the physician 120b may refer future patients to the HME provider with a higher performance.

[0091] Similarly, based on performance or compliance results of different HME providers, an insurer may choose which HME provider to partner with. Two HME providers each may accept the same insurer, e.g., Blue Cross Blue Shield. In one example, the system 100 may process a filter criterion 134 submitted by the insurer which identifies these two HME providers. The system 100 may provide a performance comparison of the two HME providers to the insurer. The insurer may choose to partner with the HME having a higher performance.5.1.1.2.2 Location Performance

[0092] The system 110 may generate performance benchmarks for different geographic locations. For example, the system 100 may indicate that virtual coaching setup works better in one location, e.g., Arizona, while in-person coaching setup works better in other locations, e.g., Florida.

[0093] In one example, the system 100 may process a filter criterion 134 that identifies a particular location. The system 100 may generate an average compliance rate of HME providers in the particular location. A physician may use such information to understand which HME provider at the particular location works best with the physician’s patient.

[0094] In another example, the system 100 may process a filter criterion 134 that identifies two or more HMD providers at a particular location. The system 100 may generate a performance comparison of these identified HME providers at the particular location.

[0095] In one example, the system 100 may process a filter criterion 134 that identifies an HMD provider at a particular location. In one instance, the processor may determine a number of compliant patients associated with the identified HME provider at the particular location. In another instance, the system 100 may determine whether the identified HME provider of a particular location performs above or below an industry benchmark. The performanceindicator generated by the system 100 may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the identified HME provider at the particular location and (2) an average ratio between a number of compliant patients and a total number of patients coached at the particular location per HME provider. For example, if the identified HME provider has three offices in the particular location, e.g., three offices in the state of Florida, the system 100 may determine that the identified HME provider may have a cumulative compliance rate of 68% in that location. The system 100 may also determine that an average HME provider in the same location has a compliance rate of 65%. As a result, the system 100 may indicate that the identified HME provider has a better performance than the industry benchmark.

[0096] In another instance, the performance indicator generated by the system 100 may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the identified HME provider at the particular location and (2) an average ratio between a number of compliant patients and a total number of patients coached at the particular location per HME provider of a patient volume similar to the identified HME provider.5.1.1.2.3 Physician Performance

[0097] Physicians who work with the same HME provider may have different performance. Some physicians may have timely follow-up protocols with patients, while other physicians may not. Physicians of a higher performance may check with patients every few days to make sure that the patients are comfortable with the HME device, whereas physicians of a lower performance may contact patients less frequently. For example, after accepting new patients, some physicians may follow up with the new patients within a few days to make sure that the new patients are all set to use an HME device, whereas other physicians may not follow up with the new patients until a month later. As a result, performance of those other physicians is relatively low, if the new patients are expected to comply with the device usage requirement starting from the first two days.

[0098] In one example, the system 100 may process a filter criterion 134 that identifies an HME provider. The system 100 may generate a performance comparison of different physicians working with the identified HME provider. Such comparison may indicate which physicians work best with the given HME provider, and may also show which physicians need to work on.

[0099] In another example, the system 100 may process a filter criterion 134 that identifies a particular physician. The system 100 may generate a performance indicator indicating a number of compliant patients, coached by the identified physician. In another instance, the system 100 may generate a performance comparison between the identified physician and the industry benchmark (e.g., an average physician performance). Such comparison may be accessed by a physician, so that the physician may obtain insights as to peer performance.

[0100] In one example, the system 100 may process a filter criterion 134 that requests performance of an identified physician across different HME providers. The system 100 may generate a performance comparison of the identified physician working with different HME providers. Using such information, the HME provider may improve its relationship with physicians having a lower performance. Further, using such information, the HME provider may also determine which physician it wants to partner with in the future.

[0101] In one example, the system may process a filter criterion 134 that identifies a physician and an HME provider. The system 100 may generate a performance indicator that includes a ratio between a number of compliant patients and a total number of patients associated with the identified HME provider and coached by the identified physician. In another example, the filter criterion 134 may request a comparison between the physician’s performance with the HME provider and an industry average. The performance indicator generated by the system 100 may indicate a comparison between ( 1 ) the ratio between a number of compliant patients and a total number of patients associated with the identified HME provider and coached by the identified physician and (2) an average ratio between a number of compliant patients and a total number of patients coached by the identified physician across the plurality of HME providers. The system 100 may output that the identified physician partnering with the identified HME provider has a compliance rate of 56%, whereas the same physician has an average compliance rate of 65% across different HME providers. Such comparison may encourage the identified HME provider to improve its relationship with the identified physician.5.1.1.2.4 Insurer Performance

[0102] Different insurers may have different workflows, some of which may be efficient, while others may be inefficient. The system may generate the performance of a given insurer, and may compare performance across different insurers. Each insurer’s performance may depend on a number or a percentage of compliant patients relative to a total number of patients associated with the insurer.

[0103] In one example, the system 100 may process a filter criterion 134 that identifies an insurer. The system 100 may output a performance indicator indicating a ratio between a number of compliant patients and a total number of patients associated with the identified insurer. In another instance, the performance indicator may indicate a comparison between (1) the ratio between a number of compliant patients and a total number of patients associated with the identified insurer and (2) an average ratio between a number of compliant patients and a total number of patients per insurer.

[0104] An insurer with a higher compliant rate may suggest that the insurer is more generous, and may thus incentivize an HME provider to partner with the high-performance insurer and / or deepen its relationship with the high-performance insurer, so as to get more reimbursements and / or discount benefits from the high-performance insurer.5.1.2 Example Flow Charts5.1.2.1 Flow Chart Related to Intra-organizational Performance Benchmarks

[0105] FIG. 3 illustrates an example flow chart for a method for monitoring performance associated with HME. At 302, the memory 104 may store information for each of a plurality of patients. The stored information for each patient may include at least one of: (1) at least one coach identifier identifying at least one coach who coaches the patient, and (2) a geographic location where the patient receives coaching from the at least one coach. At 304, at least one processor 102 may receive, from a plurality of HME devices, device usage of the plurality of patients. At 306, the at least one processor 102 may determine whether at least one of the plurality of patients is a compliant patient by comparing the device usage of the at least one patient to a device usage requirement. At 308, the at least one processor 102 may receive a filter criterion from a user. The filter criterion may include at least one selected coach identifier and / or at least one selected geographic location. At 310, the at least one processor 102 may generate a performance indicator, for output to the user, based on a number of compliant patients whose information meets the filter criterion.

[0106] In some implementations, the device usage requirement may indicate a predetermined number of device operation hours.

[0107] In some implementations, the at least one coach of each patient may include a clinician and / or a physician.

[0108] In some implementations, the performance indicator may include a ratio between the number of compliant patients and a total number of the plurality of patients.

[0109] In some implementations, the number of compliant patients may be a number of compliant patients coached by at least one coach identified by the at least one selected coach identifier.

[0110] In some implementations, the performance indicator may indicate a progression of the number of compliant patients, coached by the at least one coach identified by the at least one selected coach identifier, over time.

[0111] In some implementations, the performance indicator may indicate a comparison between the number of compliant patients, coached by the at least one coach identified by the at least one selected coach identifier and an acceptable threshold.

[0112] In some implementations, the acceptable threshold may be an average number of compliant patients per coach.

[0113] In some implementations, the at least one processor 102 may generate a message when the number of compliant patients, coached by the at least one coach identified by the at least one selected coach identifier, falls below the acceptable threshold.

[0114] In some implementations, the at least one processor 102 may send the generated message to the at least one coach identified by the at least one selected coach identifier.

[0115] In some implementations, the at least one coach identified by the at least one selected coach identifier may include at least one clinician and / or at least one physician.

[0116] In some implementations, the performance indicator may include an average number of patients per coach.

[0117] In some implementations, the number of compliant patients may be a number of compliant patients, coached at the at least one selected geographic location.

[0118]

[0119] In some implementations, the number of compliant patients may be a number of compliant patients coached by at least one coach identified by the at least one selected coach identifier at the at least one selected geographic location.

[0120] In some implementations, the at least one selected geographic location may include at least two selected geographic locations. The performance indicator may include a ratio between a number of compliant patients and a total number of patients coached at one of the at least two selected geographic locations, and a ratio between a number of compliant patients and a total number of patients coached at another one of the at least two selected geographic locations.

[0121] In some implementations, the plurality of HME devices may be provided to the plurality of patients by an HME provider.5.1.2.2 Flow Chart Related to Industry Performance Benchmarks

[0122] FIG. 4 illustrates an example flow chart of another method for monitoring performance associated with HME. At 402, the memory 104 may store information for each of a plurality of patients. The information for each patient may include at least one of: (1) an HME provider identifier identifying one of the plurality of HME providers associated with the patient, (2) a physician identifier identifying a physician who coaches the patient on using the HME device; (3) a geographic location where the patient receives coaching for using the HME device; and (4) an insurer identifier identifying an insurer associated with the patient.

[0123] At 404, at least one processor 102 may receive, from a plurality of HME devices, device usage of the plurality of patients. The HME devices may be provided to the patients by a plurality of HME providers. At 406, the at least one processor 102 may determine whether at least one of the plurality of patients is a compliant patient by comparing the device usage of the at least one patient to a device usage requirement. At 408, the at least one processor 102 may receive a filter criterion, from a user. The filter criterion may include one or more of the following: at least one selected HME provider identifier, at least one selected physician identifier, at least one selected geographic location identifier, and at least one selected insurer identifier. At 410, the at least one processor 102 may generate a performance indicator, for output to the user, based on a number of compliant patients whose information meets the filter criterion.

[0124] In some implementations, the plurality of HME providers may be of a plurality of patient volumes.

[0125] In some implementations, the at least one selected HME provider identifier may include at least two selected HME provider identifiers. The performance indicator may include a ratio between a number of compliant patients and a total number of patients associated with one of the at least two selected HME provider identifiers; and a ratio between a number of compliant patients and a total number of patients associated with another one of the at least two selected HME provider identifiers.

[0126] In some implementations, the number of compliant patients may be a number of compliant patients associated with at least one HME provider identified by the at least one selected HME provider identifier.

[0127] In some implementations, the performance indicator may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the at least one HME provider identified by the at least one selected HME provider identifier and (2) an average ratio between a number of compliant patients and a total number of patients per HME provider of a patient volume similar to the at least one HME provider identified by the at least one selected HME provider identifier.

[0128] In some implementations, the at least one processor 102 may be configured to generate a message when the ratio associated with the at least one HME provider identified by the at least one selected HME provider identifier falls below the average ratio.

[0129] In some implementations, the at least one processor 102 may send the message to the at least one HME provider identified by the at least one selected HME provider identifier.

[0130] In some implementations, the number of compliant patients may be a number of compliant patients associated with at least one HME provider identified by the at least one selected HME provider identifier, and coached at the at least one selected geographic location.

[0131] In some implementations, the performance indicator may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the at least one HME provider identified by the at least one selected HME provider identifier and coached at the at least one selected geographic location and (2) an average ratio between a number of compliant patients and a total number of patients coached at the at least one selected geographic location per HME provider.

[0132] In some implementations, the performance indicator may indicate a comparison between (1) a ratio between the number of compliant patients and a total number of patients associated with the at least one HME provider identified by the at least one selected HME provider identifier and coached at the at least one selected geographic location and (2) an average ratio between a number of compliant patients and a total number of patients coached at the at least one selected geographic location per HME provider of an patient volume similar to the at least one HME provider identified by the at least one selected HME provider identifier.

[0133] In some implementations, the number of compliant patients may be a number of compliant patients, coached by at least one physician identified by the at least one selected physician identifier

[0134] In some implementations, the performance indicator may include a ratio between a number of compliant patients and a total number of patients associated with at least one HME provider identified by the at least one HME provider identifier and coached by at least onephysician identified by the at least one selected physician identifier. In some implementations, the performance indicator may indicate a comparison between (1) the ratio calculated above and (2) an average ratio between a number of compliant patients and a total number of patients coached by at least one physician identified by the at least one selected physician identifier across the plurality of HME providers.

[0135] In some implementations, the performance indicator may include a ratio between a number of compliant patients and a total number of patients associated with at least one insurer identified by the at least one insurer identifier.

[0136] In some implementations, the performance indicator may indicate a comparison between (1) the ratio and (2) an average ratio between a number of compliant patients and a total number of patients per insurer.5.1.2.3 Example Flow Chart

[0137] FIG. 5 illustrates yet another method for monitoring performance associated with HME. At 502, the memory 104 may store information for each of a plurality of patients. At 504, at least one processor 102 may receive, from the plurality of HME devices, device usage of a plurality of patients. At 506, the at least one processor 102 may determine whether at least one of the plurality of patients is a compliant patient by comparing the device usage of the at least one patient to a device usage requirement. At 508, the at least one processor 102 may receive a filter criterion from a user. The filter criterion may concern the information. At 510, the at least one processor 102 may generate a performance indicator, for output to the user, based on a number of compliant patients whose information meets the filter criterion.

[0138] In some implementations, the information for each patient may include at least one of: (1) at least one coach identifier identifying at least one coach who coaches the patient, and (2) a geographic location where the patient receives coaching from the at least one coach.

[0139] In some implementations, the filter criterion may include at least one selected coach identifier and / or at least one selected geographic location.

[0140] In some implementations, the HME devices may be provided to the patients by a plurality of HME providers.

[0141] In some implementations, the information for each patient may include at least one of: (1) an HME provider identifier identifying one of the plurality of HME providers associated with the patient, (2) a physician identifier identifying a physician who coaches the patient on using the HME device; (3) a geographic location where the patient receives coaching for using the HME device; and (4) an insurer identifier identifying an insurer associated with the patient.

[0142] In some implementations, the filter criterion may include one or more of the following: at least one selected HME provider identifier, at least one selected physician identifier, at least one selected geographic location identifier, and at least one selected insurer identifier.

[0143] In some implementations, the performance indicator may indicate an average number of compliant patients coached by an HME provider on a monthly basis.4.1.2.4 System Architecture Flow Chart

[0144] FIG. 7 illustrates an example method of managing data using a system for evaluating therapy device usage data received from a plurality of remote therapy devices. The method may utilize the architecture of system 800a, 800b corresponding to FIGs. 6A-6B. In this regard, at block 902, the method includes receiving, such as via a network interface of the system, data such as at least in part from a plurality of remote medical devices, the data containing a plurality of data parameters. The one or more remote medical devices may be HME devices such as HME devices (e.g., HME devices 112a-l, RPT device 4000, etc.). The data may contain a plurality of data parameters. The plurality of data parameters may include usage or compliance data associated with the one or more remote medical devices. The plurality of data parameters may additionally include values such as location (e.g., clinician office, geographic, region, etc.), associated physician and / or lack of associated physician, device model, insurer, date and time a device was initialized or setup, whether or not an application on a companion device was activated) and / or other data previously described in relation to the memory 104. Additionally or alternatively, the plurality of data parameters of the data may include any other values collected or determined by the one or more remote medical devices.

[0145] At block 904, the method further includes archiving, at one or more servers, the data including the plurality of data parameters. In this regard, the one or more servers 802 may include the one or more databases 804, such as including the memory 104 previously described, and may be configured to archive the data, including a plurality of data parameters, such as the data in the memory 104 previously described.

[0146] At block 906, the method may further include receiving, such as via the network interface, a request from a remote client device. The request may relate to a predefined data subset of the plurality of data parameters. The request may be received by a service associated with the predefined data subset. In this regard, the request may be from a remote client device of the one or more remote client devices 810. The request may relate to the predefined datasubset of the plurality of data parameters. For example, the predefined data subset may include data associated with one or more criterion for evaluation of the data parameters. In one example, the requests may be filter criterion 134 and the predefined data subset may include data associated with the data parameters of the criterion. In such an example, the criterion may be at least one selected coach identifier and / or at least one selected geographic location, or other compliance related assessment as discussed herein.

[0147] At block 908, the method further includes evaluating, by a service of a plurality of services of the one or more servers of the system, data of the predefined data subset. In this regard, one of the plurality of services 806 of the one or more servers 802 may be utilized to evaluate data of the predefined data subset. At block 910, the method further includes generating, by the one of a plurality of services of the one or more servers of the system, one or more performance indicators characterizing one or more associations of the data of the predefined data subset, wherein the one or more performance indicators are based on the evaluation of the predefined data subset. In this regard, the one or more performance indicators generated by one service of the plurality of services 808 may characterize one or more associations of the data of the predefined data subset corresponding to a request and may provide a performance indication based on patient compliance information. In one example, a request may include criterion of a particular location and a particular physician. In such an example, the archived data pertaining to medical devices associated with the particular location and particular physician may be processed in a service configured for assessments directed towards location or location-based evaluations and by another service configured for assessments directed towards physicians or physician-based evaluation. In this regard, the service directed towards location may generate one or more performance indicators relating to the particular location, and the service directed towards physician may generate one or more performance indicators relating to the particular physician. The one or more performance indicators may include values determined based on the data associated with particular the criterion of the request. For example, the one or more performance indicators may include number of compliant patients, number of non-compliant patients, average time to compliance, minimum time to compliance, median time to compliance, maximum time to compliance, minimum time of non-compliance, average time of non-compliance, maximum time of non- compliance, median time of non-compliance, total number of medical devices activated, number of companion device applications activated and / or not activated, etc. Additionally or alternatively, in such an example, a service of the plurality of services may be directed towardsa combined location and physician based assessment and be configured to generate one or more performance indicators relating to both the particular physician and the particular location.

[0148] At block 912, the method further includes transmitting, such as via a network interface of the system, a report including the data of the predefined data subset and one or more performance indicators to the remote client device. In this regard, the one or more performance indicators generated at block 910 may be utilized to form a report, or performance report. The report may include the data of the predefined data subset corresponding to a request, the criterion of the request and the one or more performance indicators. The report may be indicative of one or more performance benchmarks (e.g., performance benchmarks discussed above in 4.1.1). Additionally, the service may be configured to provide the output report information in various user selectable formats such as via email, file transfer, stream, secure graphic user rendering of information, etc.5.1.3 Confidential Information

[0149] The system 100 may keep individual patient’s personal information confidential, including, but not limited to, location and device usage information of the individual patient.

[0150] The system may be configured to prevent disclosure of information between different entities such as competing entities, e.g., other HME providers or other physicians.5.1.4 Technical Advantages

[0151] The present technology may reduce burdens on healthcare systems by providing improvements in data systems and data analytics that may lead to better therapy devices, healthier patients and / or better healthcare. The present technology, such as in relation to therapy device communications and data compilation systems with electronic communication systems (e.g., networked HME devices and server-based database(s)), improves data analytics processing and / or systematic computation analysis with computational machines (i.e., computers) so as to provide technological improvement that overcome the shortfalls of existing systems.

[0152] The present technology may provide insights as to patients’ compliance regarding using HME devices, and identify problems that may affect patients’ compliance, such as to increase overall compliance rates. Such problem identification, such as based on benchmarking showing proper instruction and coaching standards are being met so as to eliminate a potential human cause for low compliance, can help lead to identification of technical causes with particular designs of therapy devices that need to be improved for greater compliance and better therapy. Moreover, given such vast data as therapy usage by vast fleets of devices, theprocesses herein can derive and generate new indicators in rapid and readily understandable presentation to permit evaluation of otherwise complex and indecipherable information.

[0153] In one aspect, by performance benchmarks, such an intra-organizational performance benchmarks, the present technology may also suggest areas of improvements to an HME provider or that no improvements are necessary. Furthermore, by knowing its current compliance benchmarks, the HME provider may strive to improve areas of weakness, which increases patient treatment (i.e., operational use of therapy devices). For example, the HME provider may arrange a clinician or a location of a higher performance to share expertise with that of a lower performance.

[0154] In another aspect, by providing industry performance benchmarks, the present technology may provide insights to different users within the patient compliance cycle as to which parties to work with and how to work with them. For example, the present disclosure may reveal to an HME provider its current performance compared to the industry standard. In turn, the HME provider may take suitable actions to improve its performance so as to stay competitive in the industry, which again increases patient treatment (i.e., operational use of therapy devices).5.2 RPT DEVICE

[0155] In some implementations, each HME device be an RPT device for treating a respiratory disorder. Referring to FIGS. 8A-9D, the RPT device 4000 may supply a flow of air to the patient 1000 via an air circuit 4170 and a patient interface 3000 or 3800.

[0156] The RPT device 4000 in accordance with one aspect of the present technology comprises mechanical, pneumatic, and / or electrical components and is configured to execute one or more algorithms 4300, such as any of the methods, in whole or in part, described herein. The RPT device 4000 may be configured to generate a flow of air for delivery to a patient’s airways, such as to treat one or more of the respiratory conditions described elsewhere in the present document.

[0157] In one form, the RPT device 4000 may be constructed and arranged to be capable of delivering a flow of air in a range of -20 L / min to +150 L / min while maintaining a positive pressure of at least 4 cmH20, or at least 10cmH2O, or at least 20 cmH2O.

[0158] With respect to FIG. 9A, the RPT device may have an external housing 4010, formed in two parts, an upper portion 4012 and a lower portion 4014. Furthermore, the external housing 4010 may include one or more panel(s) 4015. The RPT device 4000 comprises achassis 4016 that supports one or more internal components of the RPT device 4000. The RPT device 4000 may include a handle 4018.

[0159] The pneumatic path of the RPT device 4000 may comprise one or more air path items, e.g., an inlet air filter 4112, an inlet muffler 4122, a pressure generator 4140 capable of supplying air at positive pressure (e.g., a blower 4142), an outlet muffler 4124 and one or more transducers 4270, such as pressure sensors 4272 and flow rate sensors 4274.

[0160] One or more of the air path items may be located within a removable unitaiy structure which will be referred to as a pneumatic block 4020. The pneumatic block 4020 may be located within the external housing 4010. In one form a pneumatic block 4020 is supported by, or formed as part of the chassis 4016.

[0161] As shown in FIG. 9C, the RPT device 4000 may have an electrical power supply 4210, one or more input devices 4220, a central controller 4230, a therapy device controller 4240, a pressure generator 4140, one or more protection circuits 4250, memory 4260, transducers 4270, data communication interface 4280 and one or more output devices 4290. Electrical components 4200 may be mounted on a single Printed Circuit Board Assembly (PCBA) 4202. In an alternative form, the RPT device 4000 may include more than one PCBA 4202.5.2.1 RPT device mechanical & pneumatic components

[0162] An RPT device may comprise one or more of the following components in an integral unit. In an alternative form, one or more of the following components may be located as respective separate units.5.2.1.1 Air filter(s)

[0163] An RPT device in accordance with one form of the present technology may include an air filter 4110, or a plurality of air filters 4110.

[0164] In one form illustrated in FIG. 9B, an inlet air filter 4112 is located at the beginning of the pneumatic path upstream of a pressure generator 4140.

[0165] In one form illustrated in FIG. 9B, an outlet air filter 4114, for example an antibacterial filter, is located between an outlet of the pneumatic block 4020 and a patient interface 3000 or 3800.5.2.1.2 Muffler(s)

[0166] An RPT device in accordance with one form of the present technology may include a muffler 4120, or a plurality of mufflers 4120.

[0167] In one form of the present technology (see e.g., FIG. 9B), an inlet muffler 4122 is located in the pneumatic path upstream of a pressure generator 4140.

[0168] In one form of the present technology, an outlet muffler 4124 is located in the pneumatic path between the pressure generator 4140 and a patient interface 3000 or 3800.5.2.1.3 Pressure generator

[0169] In one form of the present technology, a pressure generator 4140 for producing a flow, or a supply, of air at positive pressure is a controllable blower 4142. For example, the blower 4142 may include a brushless DC motor 4144 with one or more impellers. The impellers may be located in a volute. The blower may be capable of delivering a supply of air, for example at a rate of up to about 120 litres / minute, at a positive pressure in a range from about 4 cmH2O to about 20 cmH2O, or in other forms up to about 30 cmH2O when delivering respiratory pressure therapy. The blower may be as described in any one of the following patents or patent applications the contents of which are incorporated herein by reference in their entirety: U.S. Patent No. 7,866,944; U.S. Patent No. 8,638,014; U.S. Patent No. 8,636,479; and PCT Patent Application Publication No. WO 2013 / 020167.

[0170] The pressure generator 4140 may be under the control of the therapy device controller 4240.

[0171] In other forms, a pressure generator 4140 may be a piston-driven pump, a pressure regulator connected to a high pressure source (e.g. compressed air reservoir), or a bellows.5.2.1.4 Transducer(s)

[0172] Transducers may be internal of the RPT device, or external of the RPT device. External transducers may be located for example on or form part of the air circuit, e.g., the patient interface. External transducers may be in the form of non-contact sensors such as a Doppler radar movement sensor that transmit or transfer data to the RPT device.

[0173] In one form of the present technology (see e.g., FIG. 9B), one or more transducers 4270 are located upstream and / or downstream of the pressure generator 4140. The one or more transducers 4270 may be constructed and arranged to generate signals representing properties of the flow of air such as a flow rate, a pressure or a temperature at that point in the pneumatic path.

[0174] In one form of the present technology, one or more transducers 4270 may be located proximate to the patient interface 3000 or 3800.

[0175] In one form, a signal from a transducer 4270 may be filtered, such as by low-pass, high-pass or band-pass filtering.5.2.1.4.1 Flow rate sensor

[0176] A flow rate sensor 4274 in accordance with the present technology may be based on a differential pressure transducer, for example, an SDP600 Series differential pressure transducer from SENSIRION.

[0177] In one form, a signal generated by the flow rate sensor 4274 and representing a flow rate is received by the central controller 4230.5.2.1.4.2 Pressure sensor

[0178] A pressure sensor 4272 in accordance with the present technology is located in fluid communication with the pneumatic path. An example of a suitable pressure sensor is a transducer from the HONEYWELL ASDX series. An alternative suitable pressure sensor is a transducer from the NPA Series from GENERAL ELECTRIC.

[0179] In one form, a signal generated by the pressure sensor 4272 and representing a pressure is received by the central controller 4230.5.2.1.4.3 Motor speed transducer

[0180] In one form of the present technology a motor speed transducer 4276 is used to determine a rotational velocity of the motor 4144 and / or the blower 4142. A motor speed signal from the motor speed transducer 4276 may be provided to the therapy device controller 4240. The motor speed transducer 4276 may, for example, be a speed sensor, such as a Hall effect sensor.5.2.1.5 Anti-spill back valve

[0181] As shown in FIG. 9B, one form of the present technology, an anti-spill back valve 4160 is located between the humidifier 5000 and the pneumatic block 4020. The anti-spill back valve is constructed and arranged to reduce the risk that water will flow upstream from the humidifier 5000, for example to the motor 4144.5.2.2 RPT device electrical components5.2.2.1 Power supply

[0182] A power supply 4210 may be located internal or external of the external housing 4010 of the RPT device 4000.

[0183] In one form of the present technology, power supply 4210 provides electrical power to the RPT device 4000 only. In another form of the present technology, power supply 4210 provides electrical power to both RPT device 4000 and humidifier 5000.5.2.2.2 Input devices

[0184] In one form of the present technology, an RPT device 4000 includes one or more input devices 4220 in the form of buttons, switches or dials to allow a person to interact with the device. The buttons, switches or dials may be physical devices, or software devices accessible via a touch screen. The buttons, switches or dials may, in one form, be physically connected to the external housing 4010, or may, in another form, be in wireless communication with a receiver that is in electrical connection to the central controller 4230.

[0185] In one form, the input device 4220 may be constructed and arranged to allow a person to select a value and / or a menu option.5.2.23 Central controller

[0186] In one form of the present technology, the central controller 4230 is one or a plurality of processors suitable to control an RPT device 4000. The central controller 4230 is show in FIG. 9C.

[0187] Suitable processors may include an x86 INTEL processor, a processor based on ARM® Cortex®-M processor from ARM Holdings such as an STM32 series microcontroller from ST MICROELECTRONIC. In certain alternative forms of the present technology, a 32- bit RISC CPU, such as an STR9 series microcontroller from ST MICROELECTRONICS or a 16-bit RISC CPU such as a processor from the MSP430 family of microcontrollers, manufactured by TEXAS INSTRUMENTS may also be suitable.

[0188] In one form of the present technology, the central controller 4230 is a dedicated electronic circuit.

[0189] In one form, the central controller 4230 is an application-specific integrated circuit.In another form, the central controller 4230 comprises discrete electronic components.

[0190] The central controller 4230 may be configured to receive input signal(s) from one or more transducers 4270, one or more input devices 4220, and / or the humidifier 5000.

[0191] The central controller 4230 may be configured to provide output signal(s) to one or more of an output device 4290, a pressure generator 4140, a therapy device controller 4240, a data communication interface 4280, and / or the humidifier 5000.

[0192] In some forms of the present technology, the central controller 4230 is configured to implement the one or more methodologies described herein, such as the one or more algorithms 4300 which may be implemented with processor-control instructions, expressed as computer programs stored in a non-transitory computer readable storage medium, such as memory 4260. In some forms of the present technology, the central controller 4230 may beintegrated with an RPT device 4000. However, in some forms of the present technology, some methodologies may be performed by a remotely located device. For example, the remotely located device may determine control settings for a ventilator or detect respiratory related events by analysis of stored data such as from any of the sensors described herein.5.2.2.4 Clock

[0193] The RPT device 4000 may include a clock 4232 that is connected to the central controller 4230.5.2.2.5 Therapy device controller

[0194] Referring to FIG. 9D, in one form of the present technology, therapy device controller 4240 is a therapy control module 4330 that forms part of the algorithms 4300 executed by the central controller 4230.

[0195] In one form of the present technology, therapy device controller 4240 is a dedicated motor control integrated circuit. For example, in one form a MC33035 brushless DC motor controller, manufactured by ONSEMI is used.5.2.2.6 Protection circuits

[0196] The one or more protection circuits 4250 in accordance with the present technology may comprise an electrical protection circuit, a temperature and / or pressure safety circuit.5.2.2.7 Memory

[0197] In accordance with one form of the present technology the RPT device 4000 includes memory 4260, e.g., non-volatile memory. In some forms, memory 4260 may include battery powered static RAM. In some forms, memory 4260 may include volatile RAM.

[0198] Memory 4260 may be located on the PCBA 4202. Memory 4260 may be in the form of EEPROM, or NAND flash.

[0199] Additionally, or alternatively, RPT device 4000 includes a removable form of memory 4260, for example a memory card made in accordance with the Secure Digital (SD) standard.

[0200] In one form of the present technology, the memory 4260 acts as a non-transitory computer readable storage medium on which is stored computer program instructions expressing the one or more methodologies described herein, such as the one or more algorithms 4300.5.2.2.8 Data communication systems

[0201] In one form of the present technology, a data communication interface 4280 is provided, and is connected to the central controller 4230 (see e.g., FIG. 9C). Datacommunication interface 4280 may be connectable to a remote external communication network 4282 and / or a local external communication network 4284. The remote external communication network 4282 may be connectable to a remote external device 4286. The local external communication network 4284 may be connectable to a local external device 4288.

[0202] In one form, data communication interface 4280 is part of the centred controller 4230. In another form, data communication interface 4280 is separate from the central controller 4230, and may comprise an integrated circuit or a processor.

[0203] In one form, remote external communication network 4282 is the Internet. The data communication interface 4280 may use wired communication (e.g., via Ethernet, or optical fibre) or a wireless protocol (e.g., CDMA, GSM, LTE) to connect to the Internet.

[0204] In one form, local external communication network 4284 utilises one or more communication standards, such as Bluetooth, or a consumer infrared protocol.

[0205] In one form, remote external device 4286 is one or more computers, for example a cluster of networked computers. In one form, remote external device 4286 may be virtual computers, rather than physical computers. In either case, such a remote external device 4286 may be accessible to an appropriately authorised person such as a clinician.

[0206] The local external device 4288 may be a personal computer, mobile phone, tablet or remote control.S.2.2.9 Output devices including optional display, alarms

[0207] An output device 4290 in accordance with the present technology may take the form of one or more of a visual, audio and haptic unit. A visual display may be a Liquid Crystal Display (LCD) or Light Emitting Diode (LED) display.5.2.2.9.1 Display driver

[0208] A display driver 4292 receives as an input the characters, symbols, or images intended for display on the display 4294, and converts them to commands that cause the display 4294 to display those characters, symbols, or images.5.2.2.9.2 Display

[0209] A display 4294 is configured to visually display characters, symbols, or images in response to commands received from the display driver 4292. For example, the display 4294 may be an eight-segment display, in which case the display driver 4292 converts each character or symbol, such as the figure “0”, to eight logical signals indicating whether the eight respective segments are to be activated to display a particular character or symbol.5.2.3 RPT device algorithms

[0210] As mentioned above, in some forms of the present technology, the central controller 4230 may be configured to implement one or more algorithms 4300 expressed as computer programs stored in a non-transitory computer readable storage medium, such as memory 4260. The algorithms 4300 are generally grouped into groups referred to as modules.

[0211] In other forms of the present technology, some portion or all of the algorithms 4300 may be implemented by a controller of an external device such as the local external device 4288 or the remote external device 4286. In such forms, data representing the input signals and / or intermediate algorithm outputs necessary for the portion of the algorithms 4300 to be executed at the external device may be communicated to the external device via the local external communication network 4284 or the remote external communication network 4282. In such forms, the portion of the algorithms 4300 to be executed at the external device may be expressed as computer programs, such as with processor control instructions to be executed by one or more processor(s), stored in a non-transitory computer readable storage medium accessible to the controller of the external device. Such programs configure the controller of the external device to execute the portion of the algorithms 4300.

[0212] In such forms, the therapy parameters generated by the external device via the therapy engine module 4320 (if such forms part of the portion of the algorithms 4300 executed by the external device) may be communicated to the central controller 4230 to be passed to the therapy control module 4330.5.2.3.1 Pre-processing module

[0213] A pre-processing module 4310 in accordance with one form of the present technology receives as an input a signal from a transducer 4270, for example a flow rate sensor 4274 or pressure sensor 4272, and performs one or more process steps to calculate one or more output values that will be used as an input to another module, for example a therapy engine module 4320.

[0214] In one form of the present technology, the output values include the interface pressure Pm, the vent flow rate Qv, the respiratory flow rate Qr, and the leak flow rate QI.

[0215] In various forms of the present technology, the pre-processing module 4310 comprises one or more of the following algorithms: interface pressure estimation 4312, vent flow rate estimation 4314, leak flow rate estimation 4316, and respiratory flow rate estimation 4318.5.23.1.1 Interface pressure estimation

[0216] In one form of the present technology, an interface pressure estimation algorithm 4312 receives as inputs a signal from the pressure sensor 4272 indicative of the pressure in the pneumatic path proximal to an outlet of the pneumatic block (the device pressure Pd) and a signal from the flow rate sensor 4274 representative of the flow rate of the airflow leaving the RPT device 4000 (the device flow rate Qd). The device flow rate Qd, absent any supplementary gas 4180, may be used as the total flow rate Qt. The interface pressure algorithm 4312 estimates the pressure drop AP through the air circuit 4170. The dependence of the pressure drop AP on the total flow rate Qt may be modelled for the particular air circuit 4170 by a pressure drop characteristic AP(Q). The interface pressure estimation algorithm, 4312 then provides as an output an estimated pressure, Pm, in the patient interface 3000 or 3800. The pressure, Pm, in the patient interface 3000 or 3800 may be estimated as the device pressure Pd minus the air circuit pressure drop AP.5.23.1.2 Vent flow rate estimation

[0217] In one form of the present technology, a vent flow rate estimation algorithm 4314 receives as an input an estimated pressure, Pm, in the patient interface 3000 or 3800 from the interface pressure estimation algorithm 4312 and estimates a vent flow rate of air, Qv, from a vent 3400 in a patient interface 3000 or 3800. The dependence of the vent flow rate Qv on the interface pressure Pm for the particular vent 3400 in use may be modelled by a vent characteristic Qv(Pm).5.23.13 Leak flow rate estimation

[0218] In one form of the present technology, a leak flow rate estimation algorithm 4316 receives as an input a total flow rate, Qt, and a vent flow rate Qv, and provides as an output an estimate of the leak flow rate QI. In one form, the leak flow rate estimation algorithm estimates the leak flow rate QI by calculating an average of the difference between total flow rate Qt and vent flow rate Qv over a period sufficiently long to include several breathing cycles, e.g. about 10 seconds.

[0219] In one form, the leak flow rate estimation algorithm 4316 receives as an input a total flow rate Qt, a vent flow rate Qv, and an estimated pressure, Pm, in the patient interface 3000 or 3800, and provides as an output a leak flow rate QI, by calculating a leak conductance, and determining a leak flow rate QI to be a function of leak conductance and pressure, Pm. Leak conductance is calculated as the quotient of low pass filtered non-vent flow rate equal to the difference between total flow rate Qt and vent flow rate Qv, and low pass filtered squareroot of pressure Pm, where the low pass filter time constant has a value sufficiently long to include several breathing cycles, e.g. about 10 seconds. The leak flow rate Q\ may be estimated as the product of leak conductance and a function of pressure, Pm.5.23.1.4 Respiratory flow rate estimation

[0220] In one form of the present technology, a respiratory flow rate estimation algorithm 4318 receives as an input a total flow rate, Qt, a vent flow rate, Qv, and a leak flow rate, QI, and estimates a respiratory flow rate of air, Qr, to the patient, by subtracting the vent flow rate Qv and the leak flow rate QI from the total flow rate Qt.5.23.2 Therapy Engine Module

[0221] In one form of the present technology, a therapy engine module 4320 receives as inputs one or more of a pressure, Pm, in a patient interface 3000 or 3800, and a respiratory flow rate of air to a patient, Qr, and provides as an output one or more therapy parameters.

[0222] In one form of the present technology, a therapy parameter is a treatment pressure Pt.

[0223] In one form of the present technology, therapy parameters are one or more of an amplitude of a pressure variation, a base pressure, and a target ventilation.

[0224] In various forms, the therapy engine module 4320 comprises one or more of the following algorithms: phase determination 4321, waveform determination 4322, ventilation determination 4323, inspiratory flow limitation determination 4324, apnea / hypopnea determination 4325, snore determination 4326, airway patency determination 4327, target ventilation determination 4328, and therapy parameter determination 4329.5.23.2.1 Phase determination

[0225] In one form of the present technology, the RPT device 4000 does not determine phase.

[0226] In one form of the present technology, a phase determination algorithm 4321 receives as an input a signal indicative of respiratory flow rate, Qr, and provides as an output a phase O of a current breathing cycle of a patient 1000.

[0227] In some forms, known as discrete phase determination, the phase output > is a discrete variable. Some implementations of discrete phase determination provides a bi-valued phase output <b with values of either inhalation or exhalation, for example represented as values of 0 and 0.5 revolutions respectively, upon detecting the start of spontaneous inhalation and exhalation respectively. RPT devices 4000 that “trigger” and “cycle” effectively perform discrete phase determination, since the trigger and cycle points are the instants at which thephase changes from exhalation to inhalation and from inhalation to exhalation, respectively. In some implementations of bi-valued phase determination, the phase output Q is determined to have a discrete value of 0 (thereby “triggering” the RPT device 4000) when the respiratory flow rate Qr has a value that exceeds a positive threshold, and a discrete value of 0.5 revolutions (thereby “cycling” the RPT device 4000) when a respiratory flow rate Qr has a value that is more negative than a negative threshold. The inhalation time Ti and the exhalation time Te may be estimated as typical values over many respiratory cycles of the time spent with phase equal to 0 (indicating inspiration) and 0.5 (indicating expiration) respectively.

[0228] Another implementation of discrete phase determination provides a tri-valued phase output O with a value of one of inhalation, mid-inspiratory pause, and exhalation.

[0229] In other forms, known as continuous phase determination, the phase output is a continuous variable, for example varying from 0 to 1 revolutions, or 0 to In radians. RPT devices 4000 that perform continuous phase determination may trigger and cycle when the continuous phase reaches 0 and 0.5 revolutions, respectively. In some implementations of continuous phase determination, a continuous value of phase ® is determined using a fuzzy logic analysis of the respiratory flow rate Qr. A continuous value of phase determined in this implementation is often referred to as “fuzzy phase”. In some implementations of a fuzzy phase determination algorithm 4321, the following rules are applied to the respiratory flow rate Qr'-1. If Qr is zero and increasing fast then Q is 0 revolutions.2. If Qr is large positive and steady then ® is 0.25 revolutions.3. If Qr is zero and falling fast, then is 0.5 revolutions.4. If Qr is large negative and steady then Q is 0.75 revolutions.5. If Qr is zero and steady and the 5-second low-pass filtered absolute value of Qr is large then C is 0.9 revolutions.6. If Qr is positive and the phase is expiratory, then O is 0 revolutions.7. If Qr is negative and the phase is inspiratory, then O is 0.5 revolutions.8. If the 5-second low-pass filtered absolute value of Qr is large, is increasing at a steady rate equal to the patient’s breathing rate, low-pass filtered with a time constant of 20 seconds.

[0230] The output of each rule may be represented as a vector whose phase is the result of the rule and whose magnitude is the fuzzy extent to which the rule is true. The fuzzy extent towhich the respiratory flow rate is “large”, “steady”, etc. is determined with suitable membership functions. The results of the rules, represented as vectors, are then combined by some function such as taking the centroid. In such a combination, the rules may be equally weighted, or differently weighted.

[0231] In another implementation of continuous phase determination, the phase O is first discretely estimated from the respiratory flow rate Qr as described above, as are the inhalation time Ti and the exhalation time Te. The continuous phase ® at any instant may be determined as the half the proportion of the inhalation time Ti that has elapsed since the previous trigger instant, or 0.5 revolutions plus half the proportion of the exhalation time Te that has elapsed since the previous cycle instant (whichever instant was more recent).5.23.2.2 Waveform determination

[0232] In one form of the present technology, the therapy parameter determination algorithm 4329 provides an approximately constant treatment pressure throughout a respiratory cycle of a patient.

[0233] In other forms of the present technology, the therapy control module 4330 controls the pressure generator 4140 to provide a treatment pressure Pt that varies as a function of phase of a respiratory cycle of a patient according to a waveform template 13(0).

[0234] In one form of the present technology, a waveform determination algorithm 4322 provides a waveform template 33(<1>) with values in the range [0, 1] on the domain of phase values O provided by the phase determination algorithm 4321 to be used by the therapy parameter determination algorithm 4329.

[0235] In one form, suitable for either discrete or continuously-valued phase, the waveform template 33(0) is a square-wave template, having a value of 1 for values of phase up to and including 0.5 revolutions, and a value of 0 for values of phase above 0.5 revolutions. In one form, suitable for continuously-valued phase, the waveform template n( ) comprises two smoothly curved portions, namely a smoothly curved (e.g. raised cosine) rise from 0 to 1 for values of phase up to 0.5 revolutions, and a smoothly curved (e.g. exponential) decay from 1 to 0 for values of phase above 0.5 revolutions. In one form, suitable for continuously-valued phase, the waveform template 33(0) is based on a square wave, but with a smooth rise from 0 to 1 for values of phase up to a “rise time” that is less than 0.5 revolutions, and a smooth fall from 1 to 0 for values of phase within a “fall time” after 0.5 revolutions, with a “fall time” that is less than 0.5 revolutions.

[0236] In some forms of the present technology, the waveform determination algorithm 4322 selects a waveform template 11(0) from a library of waveform templates, dependent on a setting of the RPT device. Each waveform template H(Q) in the library may be provided as a lookup table of values n against phase values d>. In other forms, the waveform determination algorithm 4322 computes a waveform template 11( ) “on the fly” using a predetermined functional form, possibly parametrised by one or more parameters (e.g. time constant of an exponentially curved portion). The parameters of the functional form may be predetermined or dependent on a current state of the patient 1000.

[0237] In some forms of the present technology, suitable for discrete bi-valued phase of either inhalation (0 = 0 revolutions) or exhalation ( = 0.5 revolutions), the waveform determination algorithm 4322 computes a waveform template II “on the fly” as a function of both discrete phase and time t measured since the most recent trigger instant. In one such form, the waveform determination algorithm 4322 computes the waveform template 11(0, f) in two portions (inspiratory and expiratory) as follows: 0 = 00 = 0.5

[0238] where Tli(Z) and HC(Z) are inspiratory and expiratory portions of the waveform template 11(0, t). In one such form, the inspiratory portion Ili(Z) of the waveform template is a smooth rise from 0 to 1 parametrised by a rise time, and the expiratory portion ne( ) of the waveform template is a smooth fall from 1 to 0 parametrised by a fall time.5.2.3.2.3 Ventilation determination

[0239] In one form of the present technology, a ventilation determination algorithm 4323 receives an input a respiratory flow rate Qr, and determines a measure indicative of current patient ventilation, Vent.

[0240] In some implementations, the ventilation determination algorithm 4323 determines a measure of ventilation Vent that is an estimate of actual patient ventilation. One such implementation is to take half the absolute value of respiratory flow rate, Qr, optionally filtered by low-pass filter such as a second order Bessel low-pass filter with a comer frequency of 0.11 Hz.

[0241] In other implementations, the ventilation determination algorithm 4323 determines a measure of ventilation Vent that is broadly proportional to actual patient ventilation. One such implementation estimates peak respiratory flow rate Qpeak over the inspiratory portion of the cycle. This and many other procedures involving sampling the respiratory flow rate Qrproduce measures which are broadly proportional to ventilation, provided the flow rate waveform shape does not vary very much (here, the shape of two breaths is taken to be similar when the flow rate waveforms of the breaths normalised in time and amplitude are similar). Some simple examples include the median positive respiratory flow rate, the median of the absolute value of respiratory flow rate, and the standard deviation of flow rate. Arbitrary linear combinations of arbitrary order statistics of the absolute value of respiratory flow rate using positive coefficients, and even some using both positive and negative coefficients, are approximately proportional to ventilation. Another example is the mean of the respiratory flow rate in the middle K proportion (by time) of the inspiratory portion, where 0 < K < 1. There is an arbitrarily large number of measures that are exactly proportional to ventilation if the flow rate shape is constant.S.2.3.2.4 Determination of Inspiratory Flow Limitation

[0242] In one form of the present technology, the central controller 4230 executes an inspiratory flow limitation determination algorithm 4324 for the determination of the extent of inspiratory flow limitation.

[0243] In one form, the inspiratory flow limitation determination algorithm 4324 receives as an input a respiratory flow rate signal Qr and provides as an output a metric of the extent to which the inspiratory portion of the breath exhibits inspiratory flow limitation.

[0244] In one form of the present technology, the inspiratory portion of each breath is identified by a zero-crossing detector. A number of evenly spaced points (for example, sixty- five), representing points in time, are interpolated by an interpolator along the inspiratory flow rate-time curve for each breath. The curve described by the points is then scaled by a scalar to have unity length (duration / period) and unity area to remove the effects of changing breathing rate and depth. The scaled breaths are then compared in a comparator with a pre-stored template representing a normal unobstructed breath. Breaths deviating by more than a specified threshold (typically 1 scaled unit) at any time during the inspiration from this template, such as those due to coughs, sighs, swallows and hiccups, as determined by a test element, are rejected. For non-rejected data, a moving average of the first such scaled point is calculated by the central controller 4230 for the preceding several inspiratory events. This is repeated over the same inspiratory events for the second such point, and so on. Thus, for example, sixty-five scaled data points are generated by the central controller 4230, and represent a moving average of the preceding several inspiratory events, e.g., three events. The moving average of continuously updated values of the (e.g., sixty-five) points are hereinafter called the "scaledflow rate ", designated as Qs(t). Alternatively, a single inspiratory event can be utilised rather than a moving average.

[0245] From the scaled flow rate, two shape factors relating to the determination of partial obstruction may be calculated.

[0246] Shape factor 1 is the ratio of the mean of the middle (e.g. thirty-two) scaled flow rate points to the mean overall (e.g. sixty-five) scaled flow rate points. Where this ratio is in excess of unity, the breath will be taken to be normal. Where the ratio is unity or less, the breath will be taken to be obstructed. A ratio of about 1.17 is taken as a threshold between partially obstructed and unobstructed breathing, and equates to a degree of obstruction that would permit maintenance of adequate oxygenation in a typical patient.

[0247] Shape factor 2 is calculated as the RMS deviation from unit scaled flow rate, taken over the middle (e.g. thirty-two) points. An RMS deviation of about 0.2 units is taken to be normal. An RMS deviation of zero is taken to be a totally flow-limited breath. The closer the RMS deviation to zero, the breath will be taken to be more flow limited.

[0248] Shape factors 1 and 2 may be used as alternatives, or in combination. In other forms of the present technology, the number of sampled points, breaths and middle points may differ from those described above. Furthermore, the threshold values can be other than those described.5.2.3.2.S Determination of apneas and hypopneas

[0249] In one form of the present technology, the central controller 4230 executes an apnea / hypopnea determination algorithm 4325 for the determination of the presence of apneas and / or hypopneas.

[0250] In one form, the apnea / hypopnea determination algorithm 4325 receives as an input a respiratory flow rate signal Qr and provides as an output a flag that indicates that an apnea or a hypopnea has been detected.

[0251] In one form, an apnea will be said to have been detected when a function of respiratory flow rate Qr falls below a flow rate threshold for a predetermined period of time. The function may determine a peak flow rate, a relatively short-term mean flow rate, or a flow rate intermediate of relatively short-term mean and peak flow rate, for example an RMS flow rate. The flow rate threshold may be a relatively long-term measure of flow rate.

[0252] In one form, a hypopnea will be said to have been detected when a function of respiratory flow rate Qr falls below a second flow rate threshold for a predetermined period of time. The function may determine a peak flow, a relatively short-term mean flow rate, or a flowrate intermediate of relatively short-term mean and peak flow rate, for example an RMS flow rate. The second flow rate threshold may be a relatively long-term measure of flow rate. The second flow rate threshold is greater than the flow rate threshold used to detect apneas.5.2.3.2.6 Determination of snore

[0253] In one form of the present technology, the central controller 4230 executes one or more snore determination algorithms 4326 for the determination of the extent of snore.

[0254] In one form, the snore determination algorithm 4326 receives as an input a respiratory flow rate signal Qr and provides as an output a metric of the extent to which snoring is present.

[0255] The snore determination algorithm 4326 may comprise the step of determining the intensity of the flow rate signal in the range of 30-300 Hz. Further, the snore determination algorithm 4326 may comprise a step of filtering the respiratory flow rate signal Qr to reduce background noise, e.g., the sound of airflow in the system from the blower.5.2.3.2.7 Determination of airway patency

[0256] In one form of the present technology, the central controller 4230 executes one or more airway patency determination algorithms 4327 for the determination of the extent of airway patency.

[0257] In one form, the airway patency determination algorithm 4327 receives as an input a respiratory flow rate signal Qr, and determines the power of the signal in the frequency range of about 0.75 Hz and about 3 Hz. The presence of a peak in this frequency range is taken to indicate an open airway. The absence of a peak is taken to be an indication of a closed airway.

[0258] In one form, the frequency range within which the peak is sought is the frequency of a small forced oscillation in the treatment pressure Pt. In some implementations, the forced oscillation is of frequency 2 Hz with amplitude about 1 cmH2O.

[0259] In one form, airway patency determination algorithm 4327 receives as an input a respiratory flow rate signal Qr, and determines the presence or absence of a cardiogenic signal. The absence of a cardiogenic signal is taken to be an indication of a closed airway.5.2.3.2.8 Determination of target ventilation

[0260] In one form of the present technology, the central controller 4230 takes as input the measure of current ventilation, Vent, and executes one or more target ventilation determination algorithms 4328 for the determination of a target value Vtgt for the measure of ventilation.

[0261] In some forms of the present technology, there is no target ventilation determination algorithm 4328, and the target value Vtgt is predetermined, for example by hard-coding during configuration of the RPT device 4000 or by manual entry through the input device 4220.

[0262] In other forms of the present technology, such as adaptive servo-ventilation (ASV), the target ventilation determination algorithm 4328 computes a target value Vtgt from a value Vtyp indicative of the typical recent ventilation of the patient.

[0263] In some forms of adaptive servo-ventilation, the target ventilation Vtgt is computed as a high proportion of, but less than, the typical recent ventilation Vtyp. The high proportion in such forms may be in the range (80%, 100%), or (85%, 95%), or (87%, 92%).

[0264] In other forms of adaptive servo-ventilation, the target ventilation Vtgt is computed as a slightly greater than unity multiple of the typical recent ventilation Vtyp.

[0265] The typical recent ventilation Vtyp is the value around which the distribution of the measure of current ventilation Vent over multiple time instants over some predetermined timescale tends to cluster, that is, a measure of the central tendency of the measure of current ventilation over recent history. In some implementations of the target ventilation determination algorithm 4328, the recent history is of the order of several minutes, but in any case should be longer than the timescale of Cheyne-Stokes waxing and waning cycles. The target ventilation determination algorithm 4328 may use any of the variety of well-known measures of central tendency to determine the typical recent ventilation Vtyp from the measure of current ventilation, Vent. One such measure is the output of a low-pass filter on the measure of cunent ventilation Vent, with time constant equal to one hundred seconds.5.23.2.9 Determination of therapy parameters

[0266] In some forms of the present technology, the central controller 4230 executes one or more therapy parameter determination algorithms 4329 for the determination of one or more therapy parameters using the values returned by one or more of the other algorithms in the therapy engine module 4320.

[0267] In one form of the present technology, the therapy parameter is an instantaneous treatment pressure Pt. In some implementations of this form, the therapy parameter determination algorithm 4329 determines the treatment pressure Pt using the equation ft = ^n( ,t)+ jp0 (1)

[0268] where:• A is the amplitude,• 11(0, t) is the waveform template value (in the range 0 to 1) at the current value of phase and t of time, and• Po is a base pressure.

[0269] If the waveform determination algorithm 4322 provides the waveform template 13(0, f) as a lookup table of values II indexed by phase the therapy parameter determination algorithm 4329 applies equation (1) by locating the nearest lookup table entry to the current value of phase returned by the phase determination algorithm 4321, or by interpolation between the two entries straddling the current value Q of phase.

[0270] The values of the amplitude A and the base pressure Po may be set by the therapy parameter determination algorithm 4329 depending on the chosen respiratory pressure therapy mode in the manner described below.5.2.3.3 Therapy Control module

[0271] The therapy control module 4330 in accordance with one aspect of the present technology receives as inputs the therapy parameters from the therapy parameter determination algorithm 4329 of the therapy engine module 4320, and controls the pressure generator 4140 to deliver a flow of air in accordance with the therapy parameters.

[0272] In one form of the present technology, the therapy parameter is a treatment pressure Pt, and the therapy control module 4330 controls the pressure generator 4140 to deliver a flow of air whose interface pressure Pm at the patient interface 3000 or 3800 is equal to the treatment pressure Pt.5.2.3.4 Detection of fault conditions

[0273] In one form of the present technology, the central controller 4230 executes one or more methods 4340 for the detection of fault conditions. The fault conditions detected by the one or more methods 4340 may include at least one of the following:• Power failure (no power, or insufficient power)• Transducer fault detection• Failure to detect the presence of a component• Operating parameters outside recommended ranges (e.g., pressure, flow rate, temperature, PaO2)• Failure of a test alarm to generate a detectable alarm signal.

[0274] Upon detection of the fault condition, the corresponding algorithm 4340 signals the presence of the fault by one or more of the following:• Initiation of an audible, visual & / or kinetic (e.g., vibrating) alarm• Sending a message to an external device• Logging of the incident5.3 AIR CIRCUIT

[0275] An air circuit 4170 in accordance with an aspect of the present technology is a conduit or a tube constructed and arranged to allow, in use, a flow of air to travel between two components such as RPT device 4000 and the patient interface 3000 or 3800.

[0276] In particular, the air circuit 4170 may be in fluid connection with the outlet of the pneumatic block 4020 and the patient interface. The air circuit may be referred to as an air delivery tube. In some cases, there may be separate limbs of the circuit for inhalation and exhalation. In other cases, a single limb is used.

[0277] In some forms, the air circuit 4170 may comprise one or more heating elements configured to heat air in the air circuit, for example to maintain or raise the temperature of the air. The heating element may be in a form of a heated wire circuit, and may comprise one or more transducers, such as temperature sensors. In one form, the heated wire circuit may be helically wound around the axis of the air circuit 4170. The heating element may be in communication with a controller such as a central controller 4230. One example of an air circuit 4170 comprising a heated wire circuit is described in United States Patent 8,733,349, which is incorporated herewithin in its entirety by reference.5.4 RESPIRATORY THERAPY MODES

[0278] Various respiratory therapy modes may be implemented by the disclosed respiratory therapy system, including but not limited to, CPAP therapy, bi-level therapy and high flow therapy, among other possibilities.5.5 GLOSSARY

[0279] For the purposes of the present technology disclosure, in certain forms of the present technology, one or more of the following definitions may apply. In other forms of the present technology, alternative definitions may apply.5.5.1 General

[0280] Air. In certain forms of the present technology, air may be taken to mean atmospheric air, and in other forms of the present technology air may be taken to mean some other combination of breathable gases, e.g. oxygen enriched air.

[0281] Ambient. In certain forms of the present technology, the term ambient will be taken to mean (i) external of the treatment system or patient, and (ii) immediately surrounding the treatment system or patient.

[0282] For example, ambient humidity with respect to a humidifier may be the humidity of air immediately surrounding the humidifier, e.g. the humidity in the room where a patient issleeping. Such ambient humidity may be different to the humidity outside the room where a patient is sleeping.

[0283] In another example, ambient pressure may be the pressure immediately surrounding or external to the body.

[0284] In certain forms, ambient (e.g., acoustic) noise may be considered to be the background noise level in the room where a patient is located, other than for example, noise generated by an RPT device or emanating from a mask or patient interface. Ambient noise may be generated by sources outside the room.

[0285] Automatic Positive Airway Pressure (APAP) therapy. CPAP therapy in which the treatment pressure is automatically adjustable, e.g. from breath to breath, between minimum and maximum limits, depending on the presence or absence of indications of SDB events.

[0286] Continuous Positive Airway Pressure (CPAP) therapy. Respiratory pressure therapy in which the treatment pressure is approximately constant through a respiratory cycle of a patient. In some forms, the pressure at the entrance to the airways will be slightly higher during exhalation, and slightly lower during inhalation. In some forms, the pressure will vary between different respiratory cycles of the patient, for example, being increased in response to detection of indications of partial upper airway obstruction, and decreased in the absence of indications of partial upper airway obstruction.

[0287] Flow rate '. The volume (or mass) of air delivered per unit time. Flow rate may refer to an instantaneous quantity. In some cases, a reference to flow rate will be a reference to a scalar quantity, namely a quantity having magnitude only. In other cases, a reference to flow rate will be a reference to a vector quantity, namely a quantity having both magnitude and direction. Flow rate may be given the symbol Q. ‘Flow rate’ is sometimes shortened to simply ‘flow’ or ‘airflow’.

[0288] In the example of patient respiration, a flow rate may be nominally positive for the inspiratory portion of a breathing cycle of a patient, and hence negative for the expiratory portion of the breathing cycle of a patient. Device flow rate, Qd, is the flow rate of air leaving the RPT device. Total flow rate, Qt, is the flow rate of air and any supplementary gas reaching the patient interface via the air circuit. Vent flow rate, Qy, is the flow rate of air leaving a vent to allow washout of exhaled gases. Leak flow rate, QI, is the flow rate of leak from a patient interface system or elsewhere. Respiratory flow rate, Qr, is the flow rate of air that is received into the patient's respiratory system.

[0289] Flow therapy. Respiratory therapy comprising the delivery of a flow of air to an entrance to the airways at a controlled flow rate referred to as the treatment flow rate that is typically positive throughout the patient’s breathing cycle.

[0290] Humidifier. The word humidifier will be taken to mean a humidifying apparatus constructed and arranged, or configured with a physical structure to be capable of providing a therapeutically beneficial amount of water (H2O) vapour to a flow of air to ameliorate a medical respiratory condition of a patient.

[0291] Leak. The word leak will be taken to be an unintended flow of air. In one example, leak may occur as the result of an incomplete seal between a mask and a patient's face. In another example leak may occur in a swivel elbow to the ambient.

[0292] Noise, conducted (acoustic)-. Conducted noise in the present document refers to noise which is carried to the patient by the pneumatic path, such as the air circuit and the patient interface as well as the air therein. In one form, conducted noise may be quantified by measuring sound pressure levels at the end of an air circuit.

[0293] Noise, radiated (acoustic)-. Radiated noise in the present document refers to noise which is carried to the patient by the ambient air. In one form, radiated noise may be quantified by measuring sound power / pressure levels of the object in question according to ISO 3744.

[0294] Noise, vent (acoustic)-. Vent noise in the present document refers to noise which is generated by the flow of air through any vents such as vent holes of the patient interface.

[0295] Oxygen enriched air. Air with a concentration of oxygen greater than that of atmospheric air (21%), for example at least about 50% oxygen, at least about 60% oxygen, at least about 70% oxygen, at least about 80% oxygen, at least about 90% oxygen, at least about 95% oxygen, at least about 98% oxygen, or at least about 99% oxygen. “Oxygen enriched air” is sometimes shortened to “oxygen”.

[0296] Medical Oxygen: Medical oxygen is defined as oxygen enriched air with an oxygen concentration of 80% or greater.

[0297] Patient: A person, whether or not they are suffering from a respiratory condition.

[0298] Pressure: Force per unit area. Pressure may be expressed in a range of units, including cmFbO, g-f7cm2and hectopascal. 1 cmFhO is equal to 1 g-f / cm2and is approximately 0.98 hectopascal (1 hectopascal = 100 Pa = 100 N / m2= 1 millibar ~ 0.001 atm). In this specification, unless otherwise stated, pressure is given in units of cmthO.

[0299] The pressure in the patient interface is given the symbol Pm, while the treatment pressure, which represents a target value to be achieved by the interface pressure Pm at the current instant of time, is given the symbol Pt.

[0300] Respiratory Pressure Therapy. The application of a supply of air to an entrance to the airways at a treatment pressure that is typically positive with respect to atmosphere.

[0301] Ventilator. A mechanical device that provides pressure support to a patient to perform some or all of the work of breathing.5.5.2 Respiratory cycle

[0302] Apnea'. According to some definitions, an apnea is said to have occurred when flow falls below a predetermined threshold for a duration, e.g. 10 seconds. An obstructive apnea will be said to have occurred when, despite patient effort, some obstruction of the airway does not allow air to flow. A central apnea will be said to have occurred when an apnea is detected that is due to a reduction in breathing effort, or the absence of breathing effort, despite the airway being patent. A mixed apnea occurs when a reduction or absence of breathing effort coincides with an obstructed airway.

[0303] Breathing rate The rate of spontaneous respiration of a patient, usually measured in breaths per minute.

[0304] Duty cycle '. The ratio of inhalation time, Ti to total breath time, Ttot.

[0305] Effort (breathing): The work done by a spontaneously breathing person attempting to breathe.

[0306] Expiratory portion of a breathing cycle: The period from the start of expiratory flow to the start of inspiratory flow.

[0307] Flow limitation'. Flow limitation will be taken to be the state of affairs in a patient's respiration where an increase in effort by the patient does not give rise to a corresponding increase in flow. Where flow limitation occurs during an inspiratory portion of the breathing cycle it may be described as inspiratory flow limitation. Where flow limitation occurs during an expiratory portion of the breathing cycle it may be described as expiratory flow limitation.

[0308] Types of flow limited inspiratory waveforms:(i) Flattened: Having a rise followed by a relatively flat portion, followed by a fall.(ii) M-shaped: Having two local peaks, one at the leading edge, and one at the trailing edge, and a relatively flat portion between the two peaks.(iii) Chair-shaped: Having a single local peak, the peak being at the leading edge, followed by a relatively flat portion.(iv) Reverse-chair shaped: Having a relatively flat portion followed by single local peak, the peak being at the trailing edge.

[0309] Hypopnea. According to some definitions, a hypopnea is taken to be a reduction in flow, but not a cessation of flow. In one form, a hypopnea may be said to have occurred when there is a reduction in flow below a threshold rate for a duration. A central hypopnea will be said to have occurred when a hypopnea is detected that is due to a reduction in breathing effort. In one form in adults, either of the following may be regarded as being hypopneas:(i) a 30% reduction in patient breathing for at least 10 seconds plus an associated 4% desaturation; or(ii) a reduction in patient breathing (but less than 50%) for at least 10 seconds, with an associated desaturation of at least 3% or an arousal.

[0310] Hyperpnecr. An increase in flow to a level higher than normal.

[0311] Inspiratory portion of a breathing cycle: The period from the start of inspiratory flow to the start of expiratory flow will be taken to be the inspiratory portion of a breathing cycle.

[0312] Patency (airway): The degree of the airway being open, or the extent to which the airway is open. A patent airway is open. Airway patency may be quantified, for example with a value of one (1) being patent, and a value of zero (0), being closed (obstructed).

[0313] Positive End-Expiratory Pressure (PEEP) '. The pressure above atmosphere in the lungs that exists at the end of expiration.

[0314] Peak flow rate (Qpeak)'. The maximum value of flow rate during the inspiratory portion of the respiratory flow waveform.

[0315] Respiratory flow rate, patient airflow rate, respiratory airflow rate (Qr) : These terms may be understood to refer to the RPT device’s estimate of respiratory flow rate, as opposed to “true respiratory flow rate” or “true respiratory flow rate”, which is the actual respiratory flow rate experienced by the patient, usually expressed in litres per minute.

[0316] Tidal volume (Vt): The volume of air inhaled or exhaled during normal breathing, when extra effort is not applied. In principle the inspiratory volume Vi (the volume of air inhaled) is equal to the expiratory volume Ve (the volume of air exhaled), and therefore a single tidal volume Vt may be defined as equal to either quantity. In practice the tidal volume Vt is estimated as some combination, e.g. the mean, of the inspiratory volume Vi and the expiratory volume Ve.

[0317] Inhalation Time (Ti) : The duration of the inspiratory portion of the respiratory flow rate waveform.

[0318] Exhalation Time (T e) : The duration of the expiratory portion of the respiratory flow rate waveform.

[0319] Total Time (Ttot) : The total duration between the start of one inspiratory portion of a respiratory flow rate waveform and the start of the following inspiratory portion of the respiratory flow rate waveform.

[0320] Typical recent ventilation: The value of ventilation around which recent values of ventilation Vent over some predetermined timescale tend to cluster, that is, a measure of the central tendency of the recent values of ventilation.

[0321] Upper airway obstruction (UAO): includes both partial and total upper airway obstruction. This may be associated with a state of flow limitation, in which the flow rate increases only slightly or may even decrease as the pressure difference across the upper airway increases (Starling resistor behaviour).

[0322] Ventilation (Vent): A measure of a rate of gas being exchanged by the patient’s respiratory system. Measures of ventilation may include one or both of inspiratory and expiratory flow, per unit time. When expressed as a volume per minute, this quantity is often referred to as “minute ventilation”. Minute ventilation is sometimes given simply as a volume, understood to be the volume per minute.5.6 OTHER REMARKS

[0323] A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in Patent Office patent files or records, but otherwise reserves all copyright rights whatsoever.

[0324] Unless the context clearly dictates otherwise and where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit, between the upper and lower limit of that range, and any other stated or intervening value in that stated range is encompassed within the technology. The upper and lower limits of these intervening ranges, which may be independently included in the intervening ranges, are also encompassed within the technology, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the technology.

[0325] Furthermore, where a value or values are stated herein as being implemented as part of the technology, it is understood that such values may be approximated, unless otherwise stated, and such values may be utilized to any suitable significant digit to the extent that a practical technical implementation may permit or require it.

[0326] Furthermore, “approximately”, “substantially”, “about”, or any similar term used herein means + / - 5-10% of the recited value.

[0327] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this technology belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present technology, a limited number of the exemplary methods and materials are described herein.

[0328] When a particular material is identified as being used to construct a component, obvious alternative materials with similar properties may be used as a substitute. Furthermore, unless specified to the contrary, any and all components herein described are understood to be capable of being manufactured and, as such, may be manufactured together or separately.

[0329] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include their plural equivalents, unless the context clearly dictates otherwise.

[0330] All publications mentioned herein are incorporated herein by reference in their entirety to disclose and describe the methods and / or materials which are the subject of those publications. The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present technology is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates, which may need to be independently confirmed.

[0331] The terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced.

[0332] The subject headings used in the detailed description are included only for the ease of reference of the reader and should not be used to limit the subject matter found throughout the disclosure or the claims. The subject headings should not be used in construing the scope of the claims or the claim limitations.

[0333] Although the technology herein has been described with reference to particular examples, it is to be understood that these examples are merely illustrative of the principles and applications of the technology. In some instances, ±e terminology and symbols may imply specific details that are not required to practice the technology. For example, although the terms "first" and "second" may be used, unless otherwise specified, they are not intended to indicate any order but may be utilised to distinguish between distinct elements. Furthermore, although process steps in the methodologies may be described or illustrated in an order, such an ordering is not required. Those skilled in the art will recognize that such ordering may be modified and / or aspects thereof may be conducted concurrently or even synchronously.

[0334] It is therefore to be understood that numerous modifications may be made to the illustrative examples and that other arrangements may be devised without departing from the spirit and scope of the technology.

Claims

6 CLAIMS1. A system architecture for evaluating therapy device usage data received from a plurality of remote therapy devices comprising: one or more servers including one or more databases, the databases containing a plurality of archived data parameters, the plurality of archived data parameters concerning data received from the plurality of remote therapy devices; the one or more servers further comprising one or more services, wherein each of the one or more services is configured to receive one or more requests relating to a respective predefined data subset of the plurality of archived data parameters, and to transmit, to a remote client device, a report including data of the respective predefined data subset and one or more performance indicators characterizing one or more associations of data of the respective predefined data subset; and wherein each of the one or more services is further configured to evaluate the respective predefined data subset based on the one or more requests to generate the one or more performance indicators based on the evaluation of the respective predefined data subset.

2. The system architecture of claim 1, wherein each of the one or more services is configured to receive the one or more requests relating to a respective predefined data subset of the plurality of archived data parameters, via a network interface.

3. The system architecture of any one of claims 1 to 2, wherein each of the one or more services of the one or more servers are configured to receive one or more requests relating to the respective predefined data subset of the plurality of archived data parameters, and to transmit, to an internal device, a report including data of the respective predefined data subset and one or more performance indicators characterizing one or more associations of data of the respective predefined data subset.

4. The system architecture of any one of claims 1 to 3, wherein the one or more requests include a filter criterion.

5. The system architecture of claim 4, wherein the filter criterion includes one or more of: a location identifier; a clinician or physician identifier; a model identifier for a remote therapydevice; a model identifier for a component used with a remote therapy device; a usage period; an insurer identifier; data indicating initial setup of a remote therapy device; and a compliance rule for usage of a remote therapy device.

6. The system architecture of any one of claims 1 to 5, wherein each service of the one or more services is configured to produce reports in a plurality of formats.

7. The system architecture of claim 6, wherein the plurality of formats includes one or more of: i) email, ii) file transfer, iii) stream, or iv) secure graphic user interface rendering of information.

8. The system architecture of any one of claims 1 to 7, wherein the one or more performance indicators comprise one or more benchmarks.

9. The system architecture of any one of claims 1 to 8, wherein one or more remote therapy devices of the plurality of remote therapy devices is a respiratory therapy device.

10. The system architecture of claim 9, wherein one or more remote therapy devices of the plurality of remote therapy devices is a positive airway pressure therapy device.1 1 . A method for evaluating therapy device usage data received from a plurality of remote therapy devices, the method including: receiving, data from the plurality of remote therapy devices, the data containing a plurality of data parameters; archiving, at one or more servers including one or more databases, the data including the plurality of data parameters into the one or more databases; receiving requests from a plurality of remote client devices, the requests relating to a predefined data subset of the plurality of data parameters; evaluating, by a service of a plurality of services of the one or more servers, data of the predefined data subset; generating, by the service of the plurality of services of the one or more servers, one or more performance indicators characterizing one or more associations of the data of thepredefined data subset, wherein the one or more performance indicators are based on the evaluation of the predefined data subset; and transmitting, in response to a request of the requests, a report including the data of the predefined data subset and the one or more performance indicators to a remote client device of the remote client devices.

12. The method of claim 11, further comprising, receiving, by the service of the plurality of services of the one or more servers, requests from one or more internal devices, the requests relating to a predefined data subset of the plurality of data parameters.

13. The method of any one of claims 11 to 12, wherein the requests relating to a predefined data subset of the plurality of data parameters includes one or more filter criterions.

14. The method of claim 13, wherein a filter criterion of the one or more filter criterions includes one or more of: a location identifier; a clinician or physician identifier; a model identifier for a remote therapy device; a model identifier for a component used with a remote therapy device; a usage period; an insurer identifier; data indicating initial setup of a remote therapy device; and a compliance rule for usage of a remote therapy device.

15. The method of any one of claims 11 to 14, further comprising, transmitting, via a network interface, the requests from the remote client devices to the service of the plurality of services.

16. The method of any one of claims 11 to 15, further comprising producing, by the service of the plurality of services, the report in a plurality of formats.

17. The method of claim 16, wherein the plurality of formats includes one or more of: i) email, ii) direct file transfer, iii) stream, and iv) secure graphic user interface rendering of information.

18. The method of any one of claims 11 to 17, wherein the one or more performance indicators comprise one or more benchmarks.

19. The method of any one of claims 11 to 18, wherein the plurality of remote therapy devices comprises respiratory therapy devices.

20. The method of claim 19, wherein the plurality of therapy devices comprises positive airway pressure therapy devices.

21. The method of any one of claims 11 to 21, wherein the receiving the requests from remote client devices is received via a network interface.

22. A processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method of evaluating therapy device usage data received from a plurality of remote therapy devices according to any one of claims 11 to 21.

23. A processor-readable medium, having stored thereon processor-executable instructions which, when executed by one or more processors, cause the one or more processors to perform a method of evaluating therapy device usage data received from a plurality of remote therapy devices, the processor-executable instructions comprising: instructions to receive, data from the plurality of remote therapy devices, the data containing a plurality of data parameters; instructions to archive, at one or more servers including one or more databases, the data including the plurality of data parameters into the one or more databases; instructions to receive requests from a plurality of remote client devices, the requests relating to a predefined data subset of the plurality of data parameters; instructions to evaluate, by a service of a plurality of services of the one or more servers, data of the predefined data subset; instructions to generate, by the service of the plurality of services of the one or more servers, one or more performance indicators characterizing one or more associations of the data of the predefined data subset, wherein the one or more performance indicators are based on the evaluation of the predefined data subset; and instructions to transmit, in response to a request of the requests, a report including the data of the predefined data subset and the one or more performance indicators to a remote client device of the remote client devices.

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