WO2023111625A1

WO2023111625A1 - Multimodal learning framework for activity-based carbon footprint prediction for healthcare, system, method, and computer program product

Info

Publication number: WO2023111625A1
Application number: PCT/IB2021/061658
Authority: WO
Inventors: Mohanasankar SIVAPRAKASAM; Keerthi Ram S.S
Original assignee: Indian Institute Of Technology Madras
Priority date: 2021-12-13
Filing date: 2021-12-13
Publication date: 2023-06-22

Abstract

The present disclosure relates to a multimodal system 100 for activity-based carbon footprint prediction contains a plurality of hospitals 102, a data repository unit 104, an information processing unit 106, an analyzing unit 108, a recommendation unit 110, a report preparation unit 112 and an output unit 114. The present disclosure also relates to a method 200 for predicting activity-based carbon footprints thereof.

Description

MULTIMODAL LEARNING FRAMEWORK FOR ACTIVITY-BASED CARBON FOOTPRINT PREDICTION FOR HEALTHCARE, SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT

TECHNICAL FIELD

The present aspect relates to data analytics unit and more particularly to information processing of administrative data records and emission data from sensors in a healthcare provider setup for predictive analytics.

BACKGROUND

Healthcare facilities operate continuously and require energy-intensive interior climate and ventilation control, related to safety and comfort of patients and staff. Standard care delivery process for most large hospitals requires significant energy use (for heating water, temperature and humidity controls for indoor air, lighting, ventilation, other clinical processes), with associated significant financial cost and GHG emissions. In India, a study of 140 multi- specialty hospitals found average consumption per unit area to be 378.kWh/m2, among the most energy-intensive commercial sectors of the country. It has been reported that healthcare’s climate footprint is equivalent to 4.4% of global net greenhouse gas emissions (2 gigatons of CO2e). This is an analytical result derived from using a global supply-chain database and performing an input-output analysis to evaluate the contribution of direct and indirect supply-chain environmental damage driven by demand in the healthcare sector.

Besides direct impact, healthcare is seen to draw on particulate matter-intensive operating inputs, such as the manufacturing of coke, and power generation. The relative proportions are direct emissions 25%, emissions occurring within the premises of immediate suppliers 25%, and distant reaches of healthcare supplychain network 50%. Between 2000 and 2015, about 25% of the particulate emissions footprint of global healthcare was associated with internationally traded goods. In financial terms, the direct environmental footprint does not follow current healthcare expenditure (CHE) - India with 3.54% of GDP CHE, has more healthcare related particulate matter footprint than Japan (10.95% GDP CHE). Additionally, GDP CHE is seen to be fairly stable over time (lOyear period), whereas direct environmental footprint is seen to be increasing.

Environmental impact assessment at the supply chain scale is largely not actionable to healthcare providers, as it is not based on monitoring, and does not provide preventive or corrective measures.

Healthcare administrative data are well-structured, rich source of information on patient journeys, evidenced care pathways, capabilities and limitations of providers, access patterns, costs, disparities, trends and insights. The information captured through claims and billing are extensive trail of events, involving procedures, consumables, interventions, drugs, and services offered by the healthcare provider, across clinical, diagnostic, therapeutic, prognostic and palliative care. This data can be mined for analyzing effort metrics, resource utilization. While at the macro scale this analysis would not provide actionable insights, the economic input-output analysis when applied at the level of individual admitted patients, individual procedures performed, and any clinical or surgical or palliative services rendered, provide information at the right granular level to integrate into actionable insights.

Therefore, in light of foregoing discussion, there is a need to develop a system to assess performance of individual clinicians and patient’s journey in order to reduce the emission.

SUMMARY OF THE INVENTION

In one aspect of an invention, a multimodal system 100 of predicting activity-based carbon footprints is provided

The system 100 contains a data repository unit 104, that receives a plurality of input data from an input unit 102 and stores the plurality of input data, an electronic information processing unit 106, that communicates with the data repository unit 104 and receives the plurality of input data from the data repository unit 104, an analyzing unit 108, that analyzes the plurality of input data received from the electronic information processing unit 106 by comparing an historic data that is stored in the data repository unit 104, a recommendation unit 110, that communicates with the analyzing unit 108 and receives an analyzed data from the analyzing unit 108, a report preparation unit 112, that communicates with the recommendation unit 110 and initiates a report based on the analyzed data and a recommended data, and an output unit 114, that communicates with the recommendation unit 110 and delivers the report prepared by the report preparation unit 112 and recommended service based on the recommended data. The plurality of input data is selected from a group comprising one or more of: a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, patient’s profile, drug database, hospital resource data, patient’s database, Clinician’s database, treatment database, diagnosis database, surgery database, medication database, pharmacy database, other management database, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country. The data repository unit 104 is a storage device and is selected from a group comprising an electronic storage device, an optical storage device, a magneto -optic al storage device, a magnetic storage device, a memory storage device, a cloud storage, a flash storage, a disk storage, or a server storage. The service is selected from a group comprising a telemonitoring service, a home care service or co-ordinate care among a hospital. The telemonitoring is provided over a communication device and are selected from a group comprising a computing device, a communications device, a handheld device, a mobile phone, a smartphone, a broadband device, a laptop, a tablet, phablet, or other wearable device. The analyzing unit 108 generates a patient’s journey and predicted emission analysis based on the anticipated events. The analyzing unit 108 accumulates the analyzed data on periodic basis to provide on- demand predictive analysis. The analyzing unit 108 analyze a carbon footprint of individual clinical procedures. The recommendation unit 110 provides an alternative recommended service to a user to reduce emission.

In another aspect of the invention, a method 200 of predicting activity-based carbon footprints is provided.

The method 200 involves collecting 202 a plurality of input data from a one or more hospitals 102 by one or more electronic computer information processors of a data repository unit 104, analyzing 204 a collected data and calculating an amount of the carbon footprints by one or more electronic computer information processors of an analyzing unit 108 to obtain analyzed data, comparing 206 the analyzed data from the analyzing unit 108 with an historic data obtained from a data repositor unit 104 to obtain a compared data, predicting 208 a recommended service to be provided to a patient or a user based on the compared data by one or more electronic computer information processors of a recommendation unit 110, preparing 210 a report based on the analyzed data provided by a report preparation unit 112 and the recommendation unit 110, and delivering 206 a recommended service to the user’s based on the user’s historic data by providing a one or more alternative recommended service in order to reduce emission. The plurality of input data is selected from a group comprising a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, patient’s profile, drug database, hospital resource data, patient’s database, Clinician’s database, treatment database, diagnosis database, surgery database, medication database, pharmacy database, other management database, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country.

In another aspect of the invention, a computer program product embodied on a computer accessible medium, including a plurality of computer instructions, which when executed on one or more electronic computer information processors performs a method 200 of predicting activity-based carbon footprints is provided.

The method 200 involves collecting 202 a plurality of input data from a one or more hospital 102 by one or more electronic computer information processors of a data repository unit 104, analyzing 204 a collected data and calculating an amount of the carbon footprints by one or more electronic computer information processors of an analyzing unit 108 to obtain analyzed data, comparing 206 the analyzed data from the analyzing unit 108 with an historic data obtained from the data repository unit 104, to obtain a compared data, predicting 208 a recommended service to be provided to a patient or a user based on the compared data by one or more electronic computer information processors of a recommendation unit 110, preparing 210 a report based on the analyzed data provided by a report preparation unit 112 and the recommendation unit 110, and delivering 206 a recommended service to the user based on the historic data by providing one or more alternative recommended service in order to reduce carbon emission. The recommended services selected from a group comprising a telemonitoring service, a home care service, a coordinate care among a hospital, a clinical service, a surgical service, a palliative service, an individual procedure, a clinical procedure, a surgical procedure; or a palliative service. The recommended services selected from a group comprising a telemonitoring service, a home care service, a co-ordinate care among a hospital, a clinical service, a surgical service, a palliative service, an individual procedure, a clinical procedure, a surgical procedure or a palliative service.

BRIEF DESCRIPTION OF DRAWINGS

The drawing/s mentioned herein disclose exemplary aspects of the claimed invention. Other objects, features, and advantages of the present invention will be apparent from the following description when read with reference to the accompanying drawing.

Figure 1 illustrates a block diagram of a multimodal system 100, according to one aspect herein;

Figure 2 illustrates a flowchart that depicts working of a multimodal system 100 of Figure 1, according to another aspect herein; and

Figure 3 illustrates an example computer system as may be used in a plurality of the devices illustrated in Figure 1.

To facilitate understanding, like reference numerals have been used, where possible to designate like elements common to the figures.

DETAILED DESCRIPTION OF PREFERRED ASPECTS

This section is intended to provide explanation and description of various possible aspects of the present invention. The aspects used herein, and the various features and advantageous details thereof are explained more fully with reference to nonlimiting aspects illustrated in the accompanying drawing/s and detailed in the following description. The examples used herein are intended only to facilitate understanding of ways in which the aspects may be practiced and to enable the person skilled in the art to practice the aspects used herein. Also, the examples/aspects described herein should not be construed as limiting the scope of the aspects herein.

As mentioned, there is a need for the development of a system to assess performance of individual clinician’s and patient’s journey observe patterns in utilization, outcomes, cost and viable substitutes. The aspect herein overcomes the limitation by providing a system to assess utilization of resources in patient’s and clinician’s granular level. The aspect also provides a machine learning unit for activity-based carbon foot print analysis and prediction in a healthcare provider facility. The term “multimodal system 100” and “system 100” and other such terms indicate a system for carbon footprint prediction and are used interchangeably.

The term “electronic information processing unit 106” and “information processing unit 106” are interchangeably used across the context.

The term “patient’s journey” defines historic events of a patient, data captured over time for a given patient, including electronic medical record data, monitored data, captured data, historical data, clinical data, etc.

The term “user” is a patient or physician/ doctor and are interchangeably used across the context.

Figure 1 illustrates a block diagram of a multimodal system 100, according to one aspect herein.

The multimodal system 100 for activity -based carbon footprint prediction contains an input unit 102, a data repository unit 104, an information processing unit 106, an analyzing unit 108, a recommendation unit 110, a report preparation unit 112 and an output unit 114.

The data repository unit 104 receives a plurality of input data from the input unit 102. In an aspect, the input unit 102 contains, not limited to, a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data. In another aspect, the patient’s transaction data includes, e.g., but not limited to, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, etc. In another aspect, the clinician’s transaction data includes, e.g., but not limited to, patient’s database, patient’s profile or drug database, etc. In another aspect resource availability data includes, e.g., but not limited to, hospital resource data, patient’s database, Clinician’s database, treatment database, diagnosis database, surgery database, medication database, pharmacy database, or other management database, etc. In another aspect, the emission data includes, e.g., but not limited to, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country, etc. In an aspect, the data repository unit 104 is a storage device. In an aspect, the storage is a cloud storage. In another aspect, the storage is a flash storage. In another aspect, the storage is a disk storage.

The information processing unit 106 communicates with the data repository unit 104 to collect an information that is collected from the set of inputs from the input unit 102.

The analyzing unit 108 analyze the input data received from the information processing unit 106 by comparing with a historic data that is stored in a data repository unit 104 via the information processing unit. In an aspect, the historic data is stored in an auxiliary storage. In an aspect, the auxiliary storage is a cloud storage. In an aspect, the auxiliary storage is a flash storage. In an aspect, the auxiliary storage is a disk storage.

The analyzing unit 108 further communicates an analyzed data to the recommendation unit 110. The recommendation unit communicates with the report preparation unit 112 to initiate a report based on the analyzed data and provides a suitable output in the output unit 114 based on the analyzed data. In an aspect, the output unit 114 communicates with a user or a patient by providing respective recommended service based on the analyzed data. In an aspect, the service includes, not limited to, telemonitoring, home care, co-ordinate care among a hospital.

In an aspect, the telemonitoring is provided by a health care worker over a communicable device. In an aspect, the communicable device includes, e.g., but not limited to, mobile phone, broadband, laptop, tablet and other wearable electronic device, etc. In an aspect, the system 100 electronically connects or couples the user or the patient with home-care providers. In an aspect, the system 100 connects or couples the user or the patients with the co-ordinate care providers. In an aspect, the system 100 provides home care and co-ordinate care based on the availability and necessity. In an aspect hospital includes, e.g., but not limited to, a local hospital, a mobile hospital, a healthcare, a med tech center, a laboratory, a relief camp or outsourcing clinic, etc.

In an aspect of an aspect, the system 100 also generates a patient’s journey and predicted analysis of anticipated events. In an aspect of an aspect, the system 100 accumulate the data per-day basis to provide on-demand predictive analysis. In an aspect of an aspect, the system 100 analyze an environmental footprint of individual clinical procedures. In an aspect of an aspect, the system 100 filters for highlighting optimal care pathways by cost, length of treatment or treatment effort involved. In an aspect of an aspect, the system 100 provides an alternative care pathway to reduce emission. In an aspect of an aspect, the system 100 utilize procedural level carbon footprint derived from administrative data. In an aspect of an aspect, the system breaks down the energy requirements at procedural level. In an aspect, the procedural level is based on patient’s profile, geographic information, hospital specialization, frequency, success rate of treating similar patients, resource availability, current resource load, etc. In an aspect of an aspect, the system 100 eliminates harm due to over-investigation and over treatment.

Figure 2 illustrates a flowchart that depicts working of a system 100 of Figure 1, according to another aspect herein. The method 200 for providing alternative care pathway is provided.

At step 202, a plurality of input data is collected from an input unit 102. In an aspect, the plurality of input data includes, e.g., but not limited to, a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, patient’s profile, drug database, hospital resource data, patient’s database, Clinician’s database, treatment database, diagnosis database, surgery database, medication database, pharmacy database, other management database, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country, etc.

At step 204, a collected data is analyzed, and an amount of carbon footprints is calculated by an analyzing unit 108.

At step 206, an analyzed data from the analyzing unit 108 is compared with an historic data to map a comparison.

At step 208, recommended service to be provided to a patient or a user is predicted based on the analyzed data by a recommendation unit 110.

At step 210, a report is prepared based on the analyzed data by report preparation unit 112 and the recommendation unit 110.

At step 212, a service is delivered to the user based on a user's history by providing an alternative ways in order to reduce emission. In an aspect, the alternative ways are the services. In another aspect, the recommended service includes, not limited to, telemonitoring, home care, co-ordinate care among a hospital.

In an aspect, figure 3 depicts a schematic illustration of an example communications and/or computing system 300 implemented according to an exemplary aspect herein.

The system 300 includes at least one processing element 310. In an aspect, the processing element is a central processing unit (CPU). According to an exemplary aspect, the CPU is coupled via a bus 305 to a memory 320. The memory 320 includes, in an exemplary aspect, a memory portion 322 that can contain instructions that when executed by the processing element 310 can perform the methods described in more detail herein. The memory 320 may be further used, according to an exemplary aspect, as a temporary storage element for the processing element 310, and/or other uses, as the case may be. The memory may comprise, in an exemplary aspect, volatile memory such as, e.g., but not limited to, a random- access memory (RAM), and/or a non-volatile memory (NVM), such as, e.g., but not limited to, Flash memory, etc., according to an exemplary aspect. Memory 320 may further include, in an exemplary aspect, a memory portion 324 containing an application program and/or application data, etc., according to an exemplary aspect. The processing element 310 may be coupled to an input 350, in one exemplary aspect. The processing element 310 may be further coupled with a database 330 and/or other storage device 330, according to an exemplary aspect. Database system and/or storage device 330, in an example aspect, can be used for the purpose of holding a copy of the method executed in accordance with the disclosed technique, according to an exemplary aspect. Database 330 may further include, e.g., but may not be limited to, a storage portion 334, which may include and/or contain subportions of an application, and/or data referenced by the application, in an exemplary aspect. In one aspect, the promotion system can be configured to execute the methods described herein with respect of the remaining figures, according to an exemplary aspect. The exemplary method, system, and/or computer program products, may be hardwired or, presented as a series of programmable instructions to be executed by the processing element 310. The principles disclosed herein can be implemented as hardware, firmware, software or any combination thereof. Moreover, the software can be implemented as an application program tangibly embodied on a program storage unit or computer readable medium. The application program may be uploaded to, and/or be executed by, a machine comprising any suitable architecture, according to an exemplary aspect. The machine may be implemented on a computer platform 300 having hardware such as, e.g., but not limited to, a processing unit (“CPU”) 310, a memory 320, and/or input interfaces 350, output interfaces (not shown), as well as other components not shown for simplicity, but as would be well known to those skilled in the relevant art, according to an exemplary aspect. The computer platform may also include, in an exemplary aspect, an operating system and/or microinstruction code. The various processes and/or functions described herein may be either part of the microinstruction code and/or part of the application program, and/or any combination thereof, which may be executed by a CPU 310, whether or not such computer and/or processor is explicitly shown, according to an exemplary aspect. In addition, various other peripheral units may be connected, and/or coupled, to the computer platform such as, e.g., but not limited to, an additional memory unit 326 and/or removable memory unit 326, an additional data storage unit 336 and/or removable storage unit 336, and a printing unit, and/or display unit, and/or other input 350, output 360, communication 370 and/or networking components 370, etc., according to an exemplary aspect.

References to “one aspect,” “an aspect,” “example aspect,” “various aspects,” “exemplary aspect,” “exemplary aspects,” etc., may indicate that the aspect(s) so described may include a particular feature, structure, or characteristic, but not every aspect necessarily includes the particular feature, structure, or characteristic. Further, repeated use of the phrase “in one aspect,” or “in an exemplary aspect,” do not necessarily refer to the same aspect, although they may.

In the following description and claims, the terms “coupled” and “connected,” along with their derivatives, may be used, according to an exemplary aspect. It should be understood that these terms are not intended as synonyms for each other. Rather, in particular aspects, “connected” may be used to indicate that two or more elements are in direct or indirect physical or electrical contact with each other, according to an exemplary aspect. “Coupled” may mean that two or more elements are in direct physical or electrical contact, according to an exemplary aspect. However, “coupled” may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other, according to an exemplary aspect.

An algorithm is here, and generally, considered to be a self-consistent sequence of acts or operations leading to a desired result, according to an exemplary aspect. These include physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated, according to an exemplary aspect. It has proven convenient at times, principally for reasons of common usage, to refer to these non-transitory signals as bits, values, elements, symbols, characters, terms, numbers or the like, according to an exemplary aspect. It should be understood, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities, according to an exemplary aspect.

Unless specifically stated otherwise, as apparent from the following discussions, it is appreciated that throughout the specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” or the like, refer to the action and/or processes of a computer or computing system, or similar electronic computing device, that manipulate and/or transform data represented as physical, such as electronic, quantities within the computing system's registers and/or memories into other data similarly represented as physical quantities within the computing system's memories, registers or other such information storage, transmission or display devices, according to an exemplary aspect.

In a similar manner, the term “processor” can refer to any device or portion of a device that processes electronic data from registers and/or memory to transform that electronic data into other electronic data that can be stored in registers and/or memory, according to an exemplary aspect. A “computing platform” can comprise one or more processors, according to an exemplary aspect. In one aspect, a processor can include an embedded processor, and/or another subsystem processor, and/or a system on a chip (SOC), device, according to an exemplary aspect.

Aspects may include apparatuses for performing the operations herein, according to an exemplary aspect. An apparatus may be specially constructed for the desired purposes, or it may comprise a general purpose and/or special purpose device selectively activated or reconfigured by a program stored in the device, according to an exemplary aspect.

Computer programs (also called computer control logic), may include computer application programs, and can include object-oriented computer programs, and can be stored in memory 320, and/or secondary memory, such as, e.g., storage 320, 322, 324, 326, 330, 334, 336 and/or removable memory and/or storage units 326, 336, also called computer program products, according to an exemplary aspect. Such computer programs, when executed, may enable the computer system 300 to perform the features as discussed herein. In particular, the computer programs, when executed, may enable the processor 310 to provide various functionality to the system 300 so as perform certain functions, according to an exemplary aspect. Accordingly, such computer programs may represent controllers of the computer system 300, according to an exemplary aspect.

In another exemplary aspect, the methods may be directed to a computer program product comprising a computer readable medium having control logic (computer software) stored therein. The control logic, when executed by the processor 310, may cause the processor 310 to perform features as described herein, according to an exemplary aspect. In another exemplary aspect which can be implemented using software, the software can be stored in a computer program product 336, 326, and can be loaded into computer system 300 using, e.g., but not limited to, the storage 330, the removable memory and/or storage device 326, 336, respectively, hard drive and/or communications and/or network interface 370, and/or router, etc. The control logic (software), when executed by the processor 310, can cause the processor 310 to perform the functions as described herein, according to an exemplary aspect. The computer software can run as a standalone software application program running atop an operating system (OS), or may be integrated into the operating system and/or application program, and/ or may be executed as an applet, or networked and/or client- server, and/or browser-based and/or other process as is well known, according to an exemplary aspect.

In yet another aspect, implementation may be primarily in hardware using, for example, but not limited to, hardware components such as, e.g., but not limited to, application specific integrated circuits (ASICs), or one or more state machines, etc., according to an exemplary aspect. Implementation of the hardware state machine so as to perform the functions described herein will be apparent to persons skilled in the relevant art(s), according to an exemplary aspect. In another exemplary aspect, as noted, implementation can be primarily in firmware.

In yet another exemplary aspect, implementation can combine any of, e.g., but not limited to, hardware, firmware, and software, etc.

Exemplary aspects may also be implemented as instructions stored on a machine- readable medium, which may be read and executed by a computing platform to perform the methods described herein. A machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine -readable medium can include read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of non-transitory propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.), memory 320, storage 330, and others, according to an exemplary aspect.

The exemplary aspects make reference to wired, and/or wireless networks, according to an exemplary aspect. Wired networks can include any of a wide variety of well-known means, or configuration to, for coupling voice and data communications devices together, according to an exemplary aspect. Similarly, any of various exemplary wireless network technologies may be used to implement the aspects discussed, according to an exemplary aspect. Specific details of wireless and/or wired communications networks are well known and are not included, as will be apparent to those of ordinary skill in the relevant art, according to an exemplary aspect.

All examples and conditional language recited herein are intended for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventor to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions, according to exemplary aspects. Moreover, all statements herein reciting principles, aspects, and aspects of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof, according to an exemplary aspect. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure, according to an exemplary aspect.

The computer-based data processing system and method described above is for purposes of example only and may be implemented in any type of computer system or programming or processing environment, or in a computer program, alone or in conjunction with hardware. The present invention may also be implemented in software stored on a computer-readable medium and executed as a computer program on a general purpose or special purpose computer, according to an exemplary aspect. For clarity, only those aspects of the system germane to the invention are described, and product details well known in the art are omitted. For the same reason, the computer hardware is not described in further detail. It should thus be understood that the invention is not limited to any specific computer language, program, communications and/or computing device, and/or computer, etc. It is further contemplated that the present invention may be run on a standalone computer system, according to an exemplary aspect, and/or may be run from a server computer system that can be accessed by a plurality of client computer systems interconnected over a network, according to an exemplary aspect, such as, e.g., but not limited to, an intranet network, internet network, etc., and/or that is accessible to clients over the global Internet, etc.. In addition, many exemplary aspects of the present invention may have application to a wide range of industries, according to an exemplary aspect. To the extent the present application discloses a system, the method implemented on a system, as well as a computer program product, such as, e.g., but not limited to, software instructions stored on a computer- readable/accessible non-transitory storage medium and executed on an electronic computer processor as a computer program to perform various steps of the method on a special purpose computer and/or in communication with other communication network devices including distributed mobile devices over one or more communication networks which may include wireless communication networks, etc., are within the scope of the present invention, according to an exemplary aspect. Further, to the extent the present application discloses a method, a system of apparatuses configured to implement the method are within the scope of the present invention, according to an exemplary aspect. While the disclosure has been presented with respect to certain specific aspects, it will be appreciated that many modifications and changes may be made by those skilled in the art without departing from the spirit and scope of the disclosure. It is intended, therefore, by the appended claims to cover all such modifications and changes as fall within the true spirit and scope of the disclosure

Claims

We Claim

1. A multimodal system (100) of predicting activity-based carbon footprints, the system (100) comprises: a data repository unit (104), that receives a plurality of input data from an input unit (102) and stores the plurality of input data; an electronic information processing unit (106), that communicates with the data repository unit (104) and receives the plurality of input data from the data repository unit (104); an analyzing unit (108), that analyzes the plurality of input data received from the electronic information processing unit (106) by comparing an historic data that is stored in the data repository unit (104); a recommendation unit (110), that communicates with the analyzing unit (108) and receives an analyzed data from the analyzing unit (108); a report preparation unit (112), that communicates with the recommendation unit (110) and initiates a report based on the analyzed data and a recommended data; and an output unit (114), that communicates with the recommendation unit (110) and delivers the report prepared by the report preparation unit (112) and recommended service based on the recommended data.

2. The system (100) as claimed in claim 1, wherein the plurality of input data is selected from a group comprising one or more of: a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, patient’s profile, drug database, hospital resource data, patient’s database, Clinician’s database, treatment database, diagnosis database, surgery database, medication database, pharmacy database, other management database, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country.

3. The system (100) as claimed in claim 1, wherein the data repository unit (104) is a storage device and is selected from a group comprising an electronic storage device, an optical storage device, a magneto-optical storage device, a magnetic storage device, a memory storage device, a cloud storage, a flash storage, a disk storage, or a server storage. . The system (100) as claimed in claim 1, wherein the service is selected from a group comprising a telemonitoring service, a home care service or co-ordinate care among a hospital.

5. The system (100) as claimed in claim 4, wherein the telemonitoring is provided over a communication device and are selected from a group comprising a computing device, a communications device, a handheld device, a mobile phone, a smartphone, a broadband device, a laptop, a tablet, phablet, or other wearable device.

6. The system (100) as claimed in claim 1, wherein the analyzing unit (108) generates a patient’s journey and predicted emission analysis based on the anticipated events. . The system (100) as claimed in claim 1, wherein the analyzing unit (108) accumulates the analyzed data on periodic basis to provide on-demand predictive analysis.

8. The system (100) as claimed in claim 1, wherein the analyzing unit (108) analyze a carbon footprint of individual clinical procedures.

9. The system (100) as claimed in claim 1, wherein the recommendation unit (110) provides an alternative recommended service to a user to reduce emission.

10. The system (100) as claimed in claim 1, wherein the recommended services selected from a group comprising a telemonitoring service, a home care service, a co-ordinate care among a hospital, a clinical service, a surgical service, a palliative service, an individual procedure, a clinical procedure, a surgical procedure or a palliative service. A method (200) of predicting activity -based carbon footprints, the method (200) comprising; collecting (202) a plurality of input data from a one or more hospitals (102) by one or more electronic computer information processors of a data repository unit (104); analyzing (204) a collected data and calculating an amount of the carbon footprints by one or more electronic computer information processors of an analyzing unit (108) to obtain analyzed data; comparing (206) the analyzed data from the analyzing unit (108) with an historic data obtained from a data repositor unit (104) to obtain a compared data; predicting (208) a recommended service to be provided to a patient or a user based on the compared data by one or more electronic computer information processors of a recommendation unit (110); preparing (210) a report based on the analyzed data provided by a report preparation unit (112) and the recommendation unit (110); and delivering (206) a recommended service to the user’s based on the user’s historic data by providing a one or more alternative recommended service in order to reduce emission. The method (200) as claimed in claim 10, wherein the plurality of input data is selected from a group comprising a patient’s transaction data, a clinician’s transaction data, a resource availability data, an emission data, a co-ordinate care data, patient’s transaction details, billing details, medication history, hospitalized history, pharmacy history, surgery history, diagnosis history, treatment history, health history or fitness history, patient’s profile, drug database, hospital resource data, patient’s database, Clinician’s database, 21 treatment database, diagnosis database, surgery database, medication database, pharmacy database, other management database, emission of a patient, emission of a clinician, emission data of a treatment, emission data of a diagnosis, emission data of a medication, emission data of a medical service, emission data of an emergency vehicle, emission of a respective department, emission of a floor, emission data of a building, emission data of a hospital data, emission data of a city, emission data of a territory or emission data of a country. A computer program product embodied on a computer accessible medium, including a plurality of computer instructions, which when executed on one or more electronic computer information processors performs a method (200) of predicting activity-based carbon footprints, the method (200) comprising; collecting (202) a plurality of input data from a one or more healthcare center (102) by one or more electronic computer information processors of a data repository unit (104); analyzing (204) a collected data and calculating an amount of the carbon footprints by one or more electronic computer information processors of an analyzing unit (108) to obtain analyzed data; comparing (206) the analyzed data from the analyzing unit (108) with an historic data obtained from the data repository unit (104), to obtain a compared data; predicting (208) a recommended service to be provided to a patient or a user based on the compared data by one or more electronic computer information processors of a recommendation unit (110); preparing (210) a report based on the analyzed data provided by a report preparation unit (112) and the recommendation unit (110); and delivering (206) a recommended service to the user based on the historic data by providing one or more alternative recommended service in order to reduce carbon emission. 22 The method (200) as claimed in claim 11, wherein the recommended services selected from a group comprising a telemonitoring service, a home care service, a co-ordinate care among a hospital, a clinical service, a surgical service, a palliative service, an individual procedure, a clinical procedure, a surgical procedure; or a palliative service. The method (200) as claimed in claim 11, wherein the healthcare sectors are selected from a group comprising a hospital, a primary health care, a secondary health care center, a tertiary health care center, a multi- specialty hospital, a clinic, a dental care unit, a scanning center, a laboratory or a med-tech center.