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Technology Overview

A-Medicare transforms and future-proof processes, services, and businesses by adopting newer digital technology, singular and blockchain databases, machine learning, big data, patient data analytics, and artificial intelligence to gain accurate insight and outcomes into drug usage, diagnosis, healthcare, and patient health lifestyles.
A software and hardware infrastructure will be developed to perform command, control, and continuous monitoring (C3M) of connected network of client hospital operations and use Internet of Things (IoT) and bionic devices worn by patients to track and analyze users’ health data. The C3M can drill down real-time data of patients such as location, chart, doctor, provider, and medical insurance when first symptoms appear and alert medical staff and contracted medical professionals.
Develop an Internet of Things (IoT) devices (similar to Fitbit or Apple Watch), and bionic nano devices such as liquid chip that is embedded into a patient skin whose electrical power is harvested from the skin temperature. These nano devices securely store selected patient 'diary' data such as PII and PHI. Once the nano device or IoT is near the vicinity of a secure Wi-Fi network, it will auto connect and new data are uploaded into a central database. The central database is continuously updated by the patient's daily activities such as exercise, drug, or medication usage, diet, and other behavioral data.
Use of the bionic and wearable devices, employ smart software tools and notification that are linked to the data warehouse, big data, and web intelligence to identify potential failures of the devices (IoT) and changes in the patient's medical data long before a symptom occurs.
Apply cybersecurity policy using blockchains, immutable ledgers, and hash techniques on selected Personally Identifiable Information (PII), Protected Health Information (PHI), diagnosis, and DNA to comply with HIPAA and other governing bodies.

Design a federated database consisting of localized databases, public and private databases, and a single A-Medicare centralized enterprise database. Integrate this federated database information by using machine learning algorithm, operations, and processes in geographical regions for performance, ethical practices, local customs, native medical practices, and more granular patient data. These data and insights are presented to doctors and decision makers on a large display's panels or iPad type devices.
Provide leadership by establishing a global alliance with insurance companies, providers, pharmaceuticals, device manufacturers, financial institutions, insurers, governments, and aid organizations to establish policies and standards in the ever-growing complexities in the healthcare practice worldwide.
Create a network of 'quick-providers' composed of front liners such as nurses, doctors, emergency medical technicians (EMT) who are in close proximity of the patient's household. The 'quick-providers' can provide immediate care of the patient during emergencies when the nearest hospital, medical clinic, or healthcare provider facility is miles and hours away. This concept is similar to Uber or Lyft ride sharing service where the nearest Lyft or Uber driver who can provide the ride is matched from the requestor's location.
Develop an early warning and tracking system to monitor organ donors worldwide and document logistics for quick and safe preparation, transportation, and transplant to a patient who is on the top priority list to receive the organ.

Federated Database and Blockchain

The A-Medicare platform will be composed of several federated, data warehouse, and blockchain databases that will initially be built or populated by health data such as epidemiological research, disease and bio hazards surveillance and other data from various sources including local data, PII, PHI, diagnostic, pharmaceutical, medical and drug research, peer-to-peer, insight, chart, patient, user profile, meta data, and data automatically sent by nano and IoT devices.
These databases will be physically hosted in various regions around the globe in a highly secure cloud infrastructure using A-Medicare's iron clad revolutionary add-on layer of cybersecurity that's impossible to hack.
Blockchain database capture general ledge data as another technique in hiding PII, PHI, diagnostic data, financial, and other healthcare data.

Medical Records, Diagnosis Data, and Charts

A-Medicare implements the cybersecurity CIA triad of Confidentiality, Integrity, and Availability. CIA protects patient's PII, PHI, diagnostics, insurance, and financial data and make this data available when needed.

Confidentiality, Integrity, and Availability

Personal medical records, charts, history archives, and documentation of doctor's visit of patient are kept securely in singular and blockchain databases both at-rest and in-transit using machine learning algorithms. This confidential data can only be accessed with 2-step authentication on top of A-Medicare ironclad designed encryption techniques on top of cybersecurity policy and other government mandated policy such as HIPAA to protect the patients PHI and PII.

Kept safe and hidden.

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Encrypted & Kept Safe

Before clear data is saved into the applicable database it is masked with A-Medicare machine learning designed algorithm. Translation code is similar to SALT in encryption to masked clear data This process will be impossible to hijack or intercept while the data is on transit to its final destination.

In seeking appointments with medical practitioners, this secure healthcare data can be accessed using authorization and 2-step authentication via browser-based and Smartphone app and A-Medicare role-base and machine learning algorithm.

Transforming Medical Records and Diagnosis Into a 'Siri' or 'Alexa' -like Voice Assistant Using Blockchain and Machine Learning Technology

For the long term, A-Medicare will design and build robots acting as Personal Health Assistants. Furthermore, A-Medicare can collaborate with robot manufacturers whose robot meets rigid specifications.

The robot should be able to understand English commands and responds accordingly such as opening the door for home healthcare service, turning on the television for news and other entertainment.

These robots can also call 911, RMTs, healthcare providers, or refill drugs. It can remind patient of medication schedule, prepare coffee, get drinks from the refrigerator, heat up food, and administer other mundane tasks in service of his/her master.

Embedded in the robot's memory are thousands of A-Medicare designed machine learning algorithm that automatically learn and improve from experience without being explicitly programmed of feed manually data or processes.

Medical Diagnostics and Genetics

Data from various A-Medicare processes and other third-party sources public and private (with prior smart contracts) are collected into a secure Data Warehouse. The aggregation of this data can be overwhelming and difficult to process especially if we’re not a medical professional. Thus, thousands of machine learning algorithms are created by A-Medicare’s Data and Machine Learning Scientists and published in a user-friendly interface accessible by authorized subscribers, researchers, doctors, and other participants.
This Data Warehouse using Big Data technology is continually updated and new information such as patient history, physical exams, diagnostic test, and hypothesis diagnosis are added. These new data are all validated and cleaned by further collections and best practices making medical diagnostics, drug usage, and other care more accurate. These data are accessible by using thousands of readily available machine learning algorithms to predict symptoms, genetics of the participants, and how it will respond to new drugs and revolutionary care or surgeries.
Use of Big Data, Federated, Data Warehouse, Blockchain databases, and artificial intelligence, coupled with the latest machine learning algorithm, can provide Data Scientists, Systems Analysts, Healthcare professionals, device manufacturers, and pharmaceuticals a more accurate insights and outcomes. Using newer digital transformation tools, the results and outcomes can prevent diseases, create new and better drugs, device new ways of analyzing diagnostic test, identifying symptoms accurately, and provide the accurate care and its costs, and invent new medical equipment.
This amalgamation of newer digital transformation tools, in the long run, saves cost to the government, insurers, hospitals, independent providers, and patients.
These set of newer digital transformation tools accessing the Federated database can also provide all the necessary information that follows PHI, PII, HIPAA, and other government policies. These tools can be used by Information Technology and Software Engineers develop applications and software modules to manage doctor’s appointments, insurance, provider, or host services such as surgeries, doctor’s visits, ICU, ER, medications, specialists, and drugs.
These healthcare resource planning programs can provide a comparison of quality care, various services, insurance premiums, cost of hospitalizations, and the right drugs for identified symptoms. The Federated database accessed by thousands of machine learning algorithms can provide insights and outcomes of user behaviors in accessing A-Medicare platform’s public as well as the user’s private information. The captured information can be sold to pharmaceutical companies, device manufacturers, hospitals, governments, insurance, marketers, and other providers. This information can be used, as an example, to develop better drugs, medical devices, and healthcare processes.
Special programs can be developed to award A-Medicare subscribers who practice healthy lifestyles. Cryptocurrency tokens can be awarded to this group of patients or subscribers who have limited use of hospital stays and doctor’s visits. The same group of users can share, if desired, their tokens to patients who badly need financial support for their surgeries, operations, and other medical needs such as home health.

Process and Machine Learning Program Warehouse

A-Medicare aims to create a library of thousands of revolutionary and novel machine learning algorithms. Ones that can:

Be ran against Big Data to track misuse, underuse, or overuse prescription drugs, detect device system failures before it happens, perform unnecessary repetitions on peoples' behalf, prevent poor communications strategy, and overcome the inefficiencies in healthcare practices.
Join publicly available healthcare and A-Medicare federated databases and warehouses to continuously update, clean, load, and transform transactions into the Data Warehouse using Big Data to provide solutions for insights and outcomes.
Identify processes and care that are safe, effective, patient-centered, timely, efficient and equitable.
Easily connects patients to healthcare practitioners and service providers.
Maps multiple autonomous database systems into a single federated databases merging several disparate and unstructured database systems into a display useful for practitioners, insurers, administrators, and patients.

Medical Diagnostics and Genetics

Data from various A-Medicare processes and other third-party sources public and private (with prior smart contracts) are collected into a secure Data Warehouse. Thousands of machine learning algorithms are created by A-Medicare Data and Machine Learning Scientists and published in a user-friendly interface accessible by authorized subscribers, researchers, doctors, and other participants.

This Data Warehouse using Big Data technology is continually updated and new information such as patient history, physical exams, diagnostic test, and hypothesis diagnosis are added. These new data are all validated and cleaned by further collections and best practices making medical diagnostics, drug usage, and other care more accurate. These data are accessible by using thousands of readily available machine learning algorithms to predict symptoms, genetics of the participants, and how it will respond to new drugs and revolutionary care or surgeries.

Use of Big Data, Federated, Data Warehouse, Blockchain databases, and artificial intelligence, coupled with the latest machine learning algorithm, can provide Data Scientists, Systems Analysts, Healthcare professionals, device manufacturers, and pharmaceuticals a more accurate insights and outcomes. Using newer digital transformation tools, the results and outcomes can prevent diseases, create new and better drugs, device new ways of analyzing diagnostic test, identifying symptoms accurately, and provide the accurate care and its costs, and invent new medical equipment.

This amalgamation of newer digital transformation tools, in the long run, saves cost to the government, insurers, hospitals, independent providers, and patients.

1. Provide all the necessary information that follows PHI, PII, HIPAA, Cybersecurity policy, and other government policies.

2. Used by Information Technology and Software Engineers to develop blockchain-based, better secure code applications and software modules to manage doctor’s appointments, insurance, provider, or host services such as surgeries, doctor’s visits, ICU, ER, medications, specialists, and drugs.

3. Provide a comparison of quality care, various services, insurance premiums, cost of hospitalizations, and the right drugs for identified symptoms.

4. Machine learning algorithms can provide insights and outcomes of user behaviors in accessing A-Medicare platform’s public as well as the user's private information.

5. Captured information can be sold to pharmaceutical companies, device manufacturers, hospitals, governments, insurance, marketers, and other providers.

6. Used, as an example, to develop better drugs, medical devices, and healthcare processes.

7. Special programs, policies, and smart contracts can be developed to award A-Medicare subscribers who practice healthy lifestyles. Cryptocurrency tokens can be awarded to this group of patients or subscribers who have limited use of hospital stays and doctor’s visits. The same group of users can share, if desired, their tokens to patients who badly need financial support for their surgeries, operations, and other medical needs such as home health.

Hardware, Software Services, and IoT Devices

A-Medicare's server-based processes will be hosted on a cloud Infrastructure as a Service (IaaS). Singular databases and Data Warehouses are PostgreSQL-based services and blockchain based distributed ledger technology (DLT). These databases securely store HIPAA mandated PHI and PII data, patient, provider, diagnosis, research, financial, advertisement, insurance, and related healthcare data.

Thousands of software web services and other processes based on SQL and machine learning algorithms drive A-Medicare platform hosting healthcare data managed by PostgreSQL.

Blockchain Technologies & Opportunities

Heavy use of machine learning and blockchain technology. The client master 'engine' will be developed around a patient-centered interface using a combination of server-, browser-, and machine learning-based algorithmic software using Python, SQL, node.js, react.js, and the Smartphone device's native operating system such as Android and Apple iOS. Develop thousands of A-Medicare designed machine learning algorithm that automatically learn and improve from experience without being explicitly programmed of feed manually data or process.

Transparency in Health Insurance Claims

Develop a process that will expedite transparency in every single health insurance claim made by a citizen into a doctor's office, specialist, hospital or medical facility (private or public) nationwide.

Develop a Fraud Early Warning System using machine learning algorithm to counteract improper practices and procedures thereby preventing fraud by medical exams, unnecessary tests, over-prescription medication, and over-billing.

Reuse Personal Medical Devices, Surplus Tokens, and Unused Drugs

Personal medical devices such as walkers, oxygen tanks, that are in perfect condition are encouraged for reuse to patients in need. This will eliminate unnecessary trash as well as help for the environment and climate change.

Patients, subscribers, and other online users who have surplus A-Medicare tokens are encouraged to voluntarily awards tokens to be used by patients who have insufficient tokens for necessary procedures.

Unused and unexpired prescription drugs can be authorized by A-Medicare doctors for use by patients especially in times of inventory stock crisis during periods of pandemic.

Givers of tokens, unused drugs and medical devices are awarded additional tokens as a good Samaritan and as a token of appreciation by the patients and A-Medicare.

Competition Amongst Healthcare Actors

Healthy competition is good for the healthcare industry and patient-centered support by providers. Competition leads further to cooperation, partnership, and joint research developing better drugs, medical devices, accurate care, and other technologies.

Competing products put down costs of drugs, medical services, and other healthcare costs without compromising quality care.

By prior agreement with competing entities, A-Medicare published information shared to competing healthcare actors can speed up care, accurate use of drugs, validation of peer-to-peer medical journal, and identification of potential diseases such as novel viruses and the best tools for contact tracing.

A-Medicare as a platform for healthcare will provide leadership by establishing alliance and convening with insurance companies, providers, pharmaceuticals, device manufacturers, financial institutions, insurers, governments, and aid organizations to establish policies and standards in the ever-growing complexities in the healthcare practice worldwide.

Visit the the platform linked at the top of the page for a brief overview of the platform and how it all fits in with AMED Coin & AMED Token