@msharmas

Founder, Editor The HCITExperts Blog

Need For A Robust ABDM Healthcare Network Enabling Cancer Care Without Walls By Manish Sharma @Msharmas

May 19, 2022 / #DIGITALHEALTH / 10 minutes of reading

The idea of expecting a doctor/physician to be responsible for keeping a patient’s health records up to date throughout his/her care journey, is obviously not preferred these days. Neither is the practice scalable nor does it allow adoption and application of recent and new technologies.

In healthcare, information about a patient/citizen is created from the moment the citizen interacts with a hospital, clinical, etc or avails of a service online. Every subsequent activity adds recency, relevancy, context of care linkage to the citizen information in that hospital’s information system. The information is filled in by any hospital employee who encounters a patient, i.e., the hospital’s front desk staff/registration person, nurse, doctor, surgeon, anesthetist, pharmacist, pathologist, radiologist, radiation oncologist, surgical oncologist, cardiologist, and many more clinicians across the continuum of care of the citizens’ journey in that facility.

In a facility it is a process of progressive elaboration that ensures the completeness of a patient record over a period of time. The scenario in a distributed network needs a healthcare network to support enable the filling of the patient/ citizen in a collaborative and participatory manner. 

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Need For A Robust ABDM Healthcare Network Enabling Cancer Care Without Walls By Manish Sharma @MsharmasRead More »

JOIN HL7 India FHIR Connectathon 2021 by HL7India Connectathon Organising Committee

May 19, 2022 / #DIGITALHEALTH / 2 minutes of reading

Greetings!

HL7 India is pleased to invite you to the second edition of the FHIR Connectathon! 

HL7 is an independent, member-based organization actively encouraging the adoption of standards of healthcare information communication in India. HL7 India is the accredited International Affiliate of Health Level Seven International (HL7 International) for India. 

After a successful FHIR Connectathon in 2020, our team at HL7 India is proud to be hosting the second edition from 10th December to 12th December 2021. Sponsored by Karkinos Healthcare Pvt. Ltd. and AliveCor India Pvt. Ltd., HL7 is proud to receive support from NRCeS and HIMSS India for this edition of FHIR Connectathon 2021. 

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JOIN HL7 India FHIR Connectathon 2021 by HL7India Connectathon Organising CommitteeRead More »

#FHIR Important Concepts, Terms and Definitions by Manish Sharma, @msharmas

June 16, 2020 / Uncategorized / 15 minutes of reading

FHIR is the latest interoperability standard based on a RESTful API architecture published by HL7. HL7 has been working for over 25 years in publishing standards for Healthcare data interoperability. The move from the earlier HL7’s 2.x standards evolved to the Development of the RIM v3 and then to FHIR, has now allowed a paradigm shift to leverage web standards. The purpose of this article is to get the reader to understand the difference between the earlier versions of HL7 interoperability standards and then present the important concepts that will help you to understand FHIR concepts, terms and definitions.

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#FHIR Important Concepts, Terms and Definitions by Manish Sharma, @msharmasRead More »

A Synopsis of MOHFW’s Guidelines for Tele-medicine Services for Ayushman Bharat Health and Wellness Centres (HWCs) by Manish Sharma, @msharmas

June 16, 2020 / TELEMEDICINE / 4 minutes of reading

The MoHFW, Government of India has published the guidelines for telemedicine services for the Ayushman Bharat – HWC. The Guidelines were notified in August, 2019. This article presents the synopsis of the guidelines.

Manoj Jhalani highlighted the need to transform 1.5 lakh PHC and SHC into Ayushman Bharat HWC(AyB-HWC) based on the Goals defined in the national health policy, 2017 to achieve universal health coverage by 2022.

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A Synopsis of MOHFW’s Guidelines for Tele-medicine Services for Ayushman Bharat Health and Wellness Centres (HWCs) by Manish Sharma, @msharmasRead More »

Glossary of terms and acronyms for #Blockchain and #Cryptocurrency

March 8, 2020 / BLOCKCHAIN / 13 minutes of reading

Blockchain: The foundational technology behind the blockchain and cryptocurrency sector. It is a virtual, immutable (unchangeable), distributed store of data stored on servers around the world. This is a new way of distributing both trust and data. It is an alternative to traditional systems where a central organization holds all the data.

Think of it as a chain of blocks of data, verified by consensus by any computer that chooses to participate. Each block of data containing anything from who has sent cryptocurrency to others to who owns what plot of land in a land registry.
Blockchain is a distributed ledger.
Block: A package of data containing multiple transactions over a given period of time.
Chain: The cryptographic link that keeps blocks together using a ‘hash’ function.
Distributed ledger: This is an analogy often made about blockchains. Instead of a centralized bank ledger, blockchains offer the promise of distributing balances throughout a network of computer servers.
You aren’t going to a single bank to store where you send your value — instead, you are going to a decentralized network of peers.
Distributed ledgers aren’t a new concept: the island of Yap used individual tables as early as 500 AD. They yelled at one another whenever they made a new transaction. Blockchains and cryptocurrencies offer the global, virtual network equivalent of that system.
Cryptocurrency: A token or currency built on top of blockchain technology. This token helps capture and distribute value from users of the blockchain. You can think of Bitcoin as the first application and cryptocurrency stemming from the blockchain. Cryptocurrencies are a subset of what are known as cryptoassets. 
Tokens: The means of exchange to give value to a transaction; typically a native cryptocurrency. Some non-currency blockchain architectures can be tokenless.
Cryptocurrency Exchange: Cryptocurrency exchanges are websites or services that let you exchange digital cryptoassets and cryptocurrencies between one another or exchange fiat currencies such as the US dollar for cryptoassets. Two of the most prominent examples of these exchanges are Coinbase and Binance.
Public/Private Keys: Keys are your way to access crypto balances and to send and receive value or data in cryptocurrency. Your public key is like your email address. It’s what allows other people to send you funds. You can share your public key with the general public.
Services like Etherscan can scan account balances and transactions associated with a public key.
Private keys are the password to your email account. Anybody who holds the private key to a wallet can access and control it and spend any tokens within it. It’s a unique string of data that represents proof of identification within the blockchain, including the right to access and own that participant’s wallet within a cryptocurrency. It must be kept secret: it is effectively a personal password
A unique string of data that identifies a participant within the blockchain. It can be shared publicly.
If you lose your private key or forget it, you’ll lose control of all the crypto assets tied to that private key/public key combination.
Cryptocurrency Wallets: Cryptocurrency wallets are ways of storing your private and public keys to your cryptoassets. A wallet is a safe you can access to then get your keys.
Wallets allow for easier access and backups if you don’t remember your private key with techniques such as the mnemonic seed phrase, a series of 25 random words you have to input to get access to your private key.
There are software wallets and hardware wallets: software wallets store your keys online, while hardware wallets use a physical device such as the Trezor to protect your private key.
MultiSig: MultiSig is a permissions system for crypto wallets. The majority of cryptocurrency wallets are single-signature. This means you only need one person’s private key to control the balance within it.
MultiSig means you need more than one private key to spend funds. This allows you to set up an M-of-M scheme. As an example, you might need 5 out of 9 signers to approve of a transaction for it to go through. This is useful for corporate wallets, where many owners and employees have to approve before a transaction is sent.
Platforms like BitGo and Xapo provide MultiSig wallets for their users.
Proof-of-work: A system where blocks of transaction data on the blockchain are mined and validated by specialized computers who earn a reward for solving specific math equations. Repeatedly running a hash function, the mechanism by which data miners win the right to add blocks to a bitcoin-style blockchain.
Mining: A practice in proof-of-work systems where computers are dedicated to solving math problems in order to claim the right to mine a block of data and to get an amount of cryptocurrency.
How it works in some more detail: the cryptographic mining piece involves solving cryptographic puzzles. A computer needs to find a nonce to combine with unverified transactions to output a verified string.
Data Mining:  The process of solving cryptographic problems using computer hardware to add newly hashed blocks to a public blockchain such as bitcoin. In fulfilling this function, successful data miners keep the blockchain actively recording transactions and, as an incentive, are awarded newly minted bitcoins for their trouble.
Mining pool: A mining pool aggregates computing resources dedicated to mining cryptocurrencies and allocates any of the mined blocks proportionally. In practice, mining cryptocurrencies has some randomness to it, so mining pools serve an essential purpose in keeping volatility down for individual miners.
Proof-of-stake: Proof-of-stake pushes people who own a selection of a blockchain’s tokens to make decisions on validating the chain. In practice, it’s a much less energy-intensive practice than mining.
Resource to read: Proof-of-stake – Wikipedia
Node: Any computing server around the world can run as a cryptocurrency node, which can store a copy of the blockchain and serve to verify transactions.
Hash The result of applying an algorithmic function to data in order to convert them into a random string of numbers and letters. This acts as a digital fingerprint of that data, allowing it to be locked in place within the blockchain.
Hash Rate: A measure of the computing power dedicated to any blockchain by the miners validating transactions and blocks. The higher the hash rate, the more active the chain is and the more appealing it is to miners. It then becomes harder to attack the chain, and infiltrate it with false transactions (known as a 51% attack).  
Decentralization: A measure of how much authority is held by a central holder. You can argue that blockchains are naturally more decentralized than other methods of distributing data because there is (at least in public chains) no gatekeeper on who can join: as long as you have the computing power, you can participate in the blockchain.
Instead of all of your data residing in one central provider (ex: Equifax), it now sits and is processed and verified by a global network of computers.
Decentralization is an ideal of the blockchain community. However, it has not been perfectly achieved.
For example, the mining pools that mine most of Bitcoin are mostly based in China: a consortium of these mining pools might decide to do what is called a 51% attack. They would use their assembled computing power to change the rules of the blockchain and facilitate conditions such as “double spend”: the ability to infinitely spend the same block of cryptocurrencies, essentially creating wealth out of nothing. The control of mining resources is very centralized.
Public vs. Private Chains: There are blockchains open entirely to the public (anybody can participate) such as Bitcoin and Ethereum. There are also private blockchains that have gatekeepers who determine who can join.
Private blockchainA closely controlled network operated by consortia in which the data is confidential and is accessed only by trusted members. Private blockchains do not require a token.
Interoperability: Blockchains and cryptocurrencies are often isolated with one another, and need to be exchanged in order to be used.  
Blockchains like Aion are looking to solve the interoperability piece by making different blockchains and cryptocurrencies interoperable, or compatible with one another: imagine, for example, a world where you can trade Bitcoin and Ethereum seamlessly (without exchanges) and use them interchangeably.
Atomic Swaps: Atomic swaps involve cryptocurrencies that are tradeable with one another without needing an exchange in the middle. Typically, they have to follow the same encryption standard and have a payment channel protocol such as Lightning Network. With what’s called a hash-time locked smart contract, two individuals can trustlessly trade cryptocurrency pairs with one another: solving the interoperability piece.  
Hash functions/tables: A more technical and precise description of the underlying technical foundation of how data is shared and stored on a blockchain. Hash tables are a mainstay of computer science.
Bitcoin: Bitcoin was created by Satoshi Nakamoto in 2008 as the first application of the blockchain and as the first cryptocurrency. It is still the dominant cryptocurrency now.
Fork: There are soft forks, where a cryptocurrency maintains its value and its rules are simply rolled forward and changed in a reversible manner, usually with the assent of the majority of the community.
Hard forks are when a blockchain fails to reach consensus and has to do a hard reset and splits off into two chains. One chain adopts one set of rules and another continues the original set of rules. This is non-reversible. A hard fork is how Bitcoin and Bitcoin Cash split.
SegWit: Segmented Witness (or SegWit) is a soft fork that happened with the Bitcoin blockchain. It solved congestion on the network by increasing the blockchain’s block size limit and splitting blocks of data in two. It separated out the unlocking signature with the scripts that send and receive data with the transactional data.
This allows the network to process more transactions per second. Users don’t have to wait as long for bitcoin transactions.
Resource to read: Segregated Witness, Part 1  
Lightning Network: Lightning Network is an off-chain solution that can settle transactions without having to use the underlying blockchain. It opens up bidirectional payment channels between different individuals, allowing Bitcoin to process many more transactions per second.
Payment channels have pre-deposited amounts of crypto placed into them. They allow individuals with channels open between them to transact seamlessly without using the blockchain. Once you get a final balance, it is validated into the blockchain.
This allows for many more payments to be done per second. It also means there is some centralization between large payers.
Resource to read: Lightning Network
Schnorr: A large Bitcoin update brewing as of the time of drafting for this article, Schnorr proposes to give users a new way to generate the private and public keys critical to cryptocurrencies. It replaces the Elliptic Curve technique currently used to generate keys with the Schnorr technique.
This update increases both privacy and security by grouping together MultiSig and regular transactions in the same category, allowing the blockchain process to more transactions and hiding whether or not a transaction is MultiSig or not.
Ethereum: The blockchain behind the second largest cryptocurrency. Ethereum differentiates itself from Bitcoin by allowing programmers to build on top of the blockchain with a Turing-complete programming language. This allows programmers to build distributed applications.
While Bitcoin can be seen as one application (transfer of value) on the distributed web just like email, Ethereum is a network that allows for many different applications to come to the fore.  
The cryptocurrency associated with the Ethereum blockchain is known as Ether.
Decentralized Apps (DApps): A decentralized application is a specific type of app that serves a specific purpose within a blockchain network. It must be open-source, autonomous, and it must make changes to the underlying software via consensus from its users. It must store all its data on a public blockchain, which is auditable by the public, and it must generate tokens and be accessible via those same tokens.
DApps seem like regular web applications. Client-side, the same mechanism is in play, but server-side (or the back-end), data and control are distributed among a network of P2P (peer-to-peer) nodes and smart contracts rather than a centralized set of servers and server code.
Resource to read: DApps – Flipside Crypto
Smart Contracts:  Smart contracts refer to code that is placed on a blockchain and is then executed on it. The code can be audited by the public. Smart contracts are often regarded as a compliment or a replacement to traditional legal contracts.
A smart contract might algorithmically implement escrow payments without having the need to create a binding legal contract to hold parties accountable.
However, the term is often seen as overly broad as it can mean any block of code placed on the blockchain.
Gas: Gas is used as a transactional cost in the Ethereum blockchain. When you use Ether to access distributed applications, you have to spend a portion of gas associated with it. Gas is correlated with how much computational work your request takes. This ensures that transactional costs are rightly set for the amount of work the system needs to do.
Gas is a way to ensure that nobody tries to attack the Ethereum network by filling it with invalid requests.
Solidity: Solidity is currently the most popular programming language to write smart contracts on the Ethereum blockchain, based around EMCAScript (the basis of JavaScript).
DAO: DAOs or decentralized autonomous organizations are a collective grouping in which smart contracts make choices. The entire organization is run on the blockchain. Shareholders buy tokens that give them the right to vote on future decisions.
Resource to read: DAO – Flipside Crypto
Casper:  Casper is an implementation of the Ethereum blockchain that promises to process more transactions per second. Ethereum used to be able to process 20 transactions a second. Bitcoin could only process 4. Visa and Mastercard can process about 20000 transactions a second. Casper is an in-between step for the Ethereum blockchain to change over from proof-of-work to proof-of-stake. It implements sharding (dividing the main Ethereum chain into smaller subcomponent chains) to provide parallel processing and increased throughput.
ERC20: A set of standards based on the Ethereum blockchain. ERC20 allows anybody to create a token built on top of Ethereum’s blockchain. It is the basis of the initial coin offering craze and the advent of new “altcoins”.
Altcoins: Altcoins are tokens, cryptocurrencies and cryptoassets outside of Bitcoin and Ethereum. Coinmarketcap gives you a good view of how many there are!
Stablecoins: Stablecoins are cryptoassets pegged to a certain value or asset — for example, you have stablecoins that trade 1:1 with the US dollar. These are collateralized or not with other cryptoassets.
Initial Coin Offering: Another way to originate tokens for a blockchain. An ICO involves a marketing process, private sale, then a public sale of a newly-listed token, which then aims to be listed on as many cryptocurrency exchanges as possible. Note that there is no standard way of conducting initial coin offerings.
Hyperledger An umbrella project set up by the Linux Foundation comprising various tools and systems for building open-source blockchains.
Oracle: A bridge from a blockchain to an external data source that allows a smart contract to complete its business by referencing timely real-world information. An oracle might allow a smart contract to access consumer energy usage, live train timetables, election results, and so on.
Peer-to-peer (P2P)The direct sharing of data between nodes on a network, as opposed to via a central server. 
Permissioned ledgerA large, distributed network using a native token, with access restricted to those with specific roles.
Proof of stake The mechanism by which participants earn the right to add new blocks and so earn new tokens, based on how much of that currency they already hold.
Public blockchainA large distributed network using a native token (such as bitcoin), open to everyone to participate and maintain.

References: 

[1]: A definitive glossary of blockchain and cryptocurrency terms: 
https://thenextweb.com/contributors/2018/08/21/a-definitive-glossary-of-blockchain-and-cryptocurrency-terms/

[2]: Flipside Crypto’s guide to blockchain and cryptocurrencies:  https://flipsidecrypto.com/wealthadvisor-ebook/
Team @HCITExperts [Updated: 1st Sep 2018]
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Your partner in Digital Health Transformation using innovative and insightful ideas

Zen Clinicals: An Activity & Workflow based solution (2 of 4)

March 28, 2020 / Uncategorized / 1 minute of reading


 Part 2 of 4

Now that we have defined the various actors and the activities that they could be performing. It becomes to important to define the guidance as to how these activities will be delivered to their respective audiences. 

In the Zen Clinical System 

Zen Clinicals: An Activity & Workflow based solution (3 of 4)

March 28, 2020 / Uncategorized / 1 minute of reading



 Part 3 of 4

Sharing some of the UI screens that I had envisaged for the Zen Clinicals system. The core premise of the system is to be data driven and workflow driven and NOT BE a transactional system wherein a sequential set of activities or tasks are carried out.

 Zen Clinicals ensures there are actionable insights that are presented to the right care providers at the right time. 

 Welcome you to review the first two parts of this blog: 

 Part 1: https://blog.hcitexpert.com/2015/12/zen-clinicals-1of3.html

 Part 2: https://blog.hcitexpert.com/2018/07/zen-clinicals-patient-care-pathways-by-manish-sharma.html

Zen Clinicals: A Patient Care Pathways Solution (4 of 4)

March 8, 2020 / Uncategorized / 6 minutes of reading

A Clinical Care Pathways Workflow & Activity Orchestration

Overview

Clinical pathways are structured multidisciplinary care plans which address specific clinical scenarios and help to standardize and coordination of care.
The patient care pathways solutions have become an important clinical guidelines implementation tools in hospital settings. They have the ability to provide, not only a standardised care to the patients’ presenting same/ similar diagnosis, but also provide the ability to handle the variance from the defined care pathways for various specialties and diagnosis.
The care pathways also provides the ability to coordinate care of a patient across various user groups and user roles, like the group of nurses across shifts and across roles like doctors, nurses and administrative staff.
The Care Pathways aim to optimize the efficiency and quality of care
The care pathways solution that we propose to develop have the following features.

Clinical Data Repository

At the heart of our Patient Care Pathways solution is a clinical data repository that maintains a longitudinal patient care record. The Patient CDR is a data warehouse of the Patient’s clinical data that has been stored in the clinical data repository to enable data analysis across the patient episodes and visits.
The Clinical Data Repository provides the ability to organically analyse data from ‘similar’ patients across same or similar set of data points like diagnosis, test results and clinical studies.
The clinical data repository converts all the data captured in various connected systems to a analysable data point for the care pathways solution. The data captured in the external system
The clinical data repository is a the heart of the care pathways solution that contains information that has been stored in standardised format using the standard healthcare coding systems like ICD10, SNOMED CT, ICD10 PCS and others as applicable in the clinical scenario.
In-built into the Clinical Data Repository are latest big data analytics capabilities that are required to generate the statistical analysis of the adherence to the quality and efficincy of the Care Pathway.
The clinical data repository has the ability to generate, out of the box, all the analytical reports and predictive modelling required for todays’ clinicians to make the right decisions at the right time.
The Clinical Data Repository allows for the following features and functionalities that are relevant to the Care Pathways solution
  1. Allows for analysing historical outcomes from clinically similar patients, e.g. patients like me type of scenario matching
  2. Display the variance and outcomes for the patient specific pathway and across various patients

Care Pathways Designer

The Care Pathways designer is a visual tool that allows the user to define the workflow of activities based on a start condition. The Start Up condition for a Care Pathway could be a Code Red alarm for quarantine or it could be a set of questions that a care provider answers to based on the patient they are treating for, for instance, chest pain.
The Care pathways designer has at its core the following:
  1. Activities
  2. Activity Groups
  3. Users
  4. User Groups
  5. Workflow Designer
Care Pathways Designer Features:
  1. The care pathways designer is a tool that allows the care pathways design team to define the standardised care templates of activities that should be scheduled for a patient presenting a chief complaint or being treated for a chronic condition.
  2. The care pathways designer has a set of pre-defined activity categories. For example, Appointment Scheduling, Laboratory Orders, Radiology Orders, Pharmacy Orders and many more. Each of the activity categories are defined based on the corresponding activity that needs to be instantiated at the host system, such as an EHR or a HIMS Solution. The Patient Care Pathways solution allows the users to define these activity categories depending on the host system.
  3. The Care Pathways Designer tool allows the users to define the workflow for the care pathways. The tool allows the user to define rules and the activities (or activity groups) that will be instantiated depending on the condition of the rule.
  4. The Care Pathways designer tool also has the ability to define various outcomes and the activities that need to be performed to achieve those outcomes.

Rules Designer

The clinical pathways designer will have a rules designer that allows the users to select the various activities and activities groups to be the outcome and action targets for a clinical rule.
For instance, if the doctor selects a certain type of schedule H drugs to be ordered for a patient and the doctor does not have the authorization to order schedule H drugs, the order will be sent to the next level of authorization within the patient care team.
The rules can be included into the care pathways designer as workflow activities and decision criteria.

User & User Group based Task Lists

The system will have a user specific task list that will inform the user on the various activities that a user (nurse, doctor, admissions and billing users) needs to perform vis-a-vis a patient. The Task list will help the user to complete the tasks that have been generated based on the various active care pathways for the various patients.
The system also has the ability to share the generated tasks between a group of care providers. This allows for the nurses taking care of the patients across the various shifts to review the tasks that have been completed or not completed during an earlier shift.

Care Pathway Dashboard

The system will have a comprehensive Care Pathway Dashboard. The dashboard will display the following:
  1. The Care Pathway adherence Index displays the variance or conformance of a care pathway when applied to multiple patients.
  2. The Care Pathway patient adherence Index, this displays the effectiveness of a care plan when applied to a specific patient.
In both the above scenarios, the care plan adherence Index will display the deviations, the variances and adherence levels to the defined care plan. It will also list out the activities that were done in addition or in variance of a defined care plan.
In addition to the variance and conformance metrics the Care Pathway Dashboards will display to the users the following:
  1. The Patient Specific Care Pathway Activity Scheduler: Displays the day by day list of all the activities that have been defined (scheduled) in a care plan. It also has the ability to showcase the activities by a shift.
  2. Care Pathway timeline: Displays the care plan timeline and recorded variance and non-conformance detection
  3. Outcomes Recording: The Care Pathway solution also allows the users to record the outcomes for each of the planned activities and the Outcomes defined for the Care Pathway.

Care Pathway Push Notifications & Alerts Center

The Care Pathway Push Notifications and Alerts center is an important part of our solution. The Care Pathway push notification system identifies the most important and high priority tasks that need to be performed for each of the patients. The users are alerted about these high priority tasks on their associated mobile devices.
The Care Pathway Push Notifications have been designed to be non-obstrusive and presented in a way the user has configured these to be delivered to them. This is done to ensure there is no alert-fatigue generated based on our notifications and alerts center.
In addition to the Push Notification for tasks to be performed on a high priority, the Care Pathways solution also has the ability to provide alerts of outstanding or upcoming, completed or activities in variance of the defined Care Pathway to relevant team members.
Each alert and push notification will be configured with a level of priority (that can be assigned to the alert type or determined by the system) and depending on the Level of Priority of that alert and notification, the system will present the alert to the user.

Additional Resources & Standards Definitions:

  1. The care pathway models in the tool are based on the following industry standards:
    1. OMG Case Management Model and Notation (CMMN), and
    2. HL7 GELLO and
    3. vMR

Care Pathway Examples:

carepathwaychestpain.gif
Suspected Heart Failure.gif

2018 Internet Trends Rerport by Mary Meeker @KPCB

March 8, 2020 / SURVEY REPORTS / 2 minutes of reading


Review the Mary Meeker 2018 Internet Report to understand the most important technology statistics and trends. Legendary Venture Capitalist has released the 2018 Internet Report covering insights about mobile, commerce, competition between Tech Giants, Freelance workers, Job Trends, Healthcare spend, and many other aspects in the entire 294 page report.

Context via KPCB 2018 Internet Trends Report:


“We use data to tell stories of business-related trends we focus on. We hope others take the ideas, build on them & make them better.  

At 3.6B, the number of Internet users has surpassed half the world’s population. When markets reach mainstream, new growth gets harder to find – evinced by 0% new smartphone unit shipment growth in 2017. 

Internet usage growth is solid while many believe it’s higher than it should be. Reality is the dynamics of global innovation & competition are driving product improvements, which, in turn, are driving usage & monetization. Many usability improvements are based on data – collected during the taps / clicks / movements of mobile device users. This creates a privacy paradox… 

Internet Companies continue to make low-priced services better, in part, from user data. Internet Users continue to increase time spent on Internet services based on perceived value. Regulators want to ensure user data is not used ‘improperly.’

Scrutiny is rising on all sides – users / businesses / regulators. Technology-driven trends are changing so rapidly that it’s rare when one side fully understands the other…setting the stage for reactions that can have unintended consequences. And, not all countries & actors look at the issues through the same lens. 

We focus on trends around data + personalization; high relative levels of tech company R&D + Capex Spending; E-Commerce innovation + revenue acceleration; ways in which the Internet is helping consumers contain expenses + drive income (via on-demand work) + find learning opportunities.  

We review the consumerization of enterprise software and, lastly, we focus on China’s rising intensity & leadership in Internet-related markets.”


Here’s the link to our review of the 2017 Internet Trends Report by Mary Meeker: 
https://blog.hcitexpert.com/2017/06/digitalhealth-at-inflection-point.html

@HIMSSIndia 2018 Conference and Exhibition, Bengaluru #HIMSSIndia

March 8, 2020 / CONFERENCES / 2 minutes of reading

HIMSS India 2018: Annual Conference and Exhibition  will bring together key stakeholders from Government, Statutory Bodies, Healthcare Providers, Payers, Life Sciences, Medical Device, Healthcare IT and solution providers for path-breaking collaborative discussions on healthcare IT issues, best practices and the latest in tools & technologies that will drive and enhance the new age healthcare delivery and outcomes.

Why Attend

Exceptional education, world class speakers, cutting-edge healthcare IT products and powerful networking are hallmarks of this industry leading show. Attending HIMSS India Annual Conference provides an unparalleled opportunity for you to learn and experience the latest developments and trends emerging in Healthcare IT. The event will showcase how IT is transforming the full spectrum of the continuum of care. This conference will deliver insights for healthcare stakeholders to better understand the future market drivers, emerging business trends and technology opportunities impacting the healthcare IT market in India. 

  • Understand the emerging healthcare IT landscape and how it would impact medical practice and healthcare delivery 
  • High-value education and network opportunities with Government and private stakeholders 
  • Identify the latest technologies and their impact on healthcare IT 
  • Meet and interact with the leaders driving the change 
  • Insight in Emerging Technologies like AI, Population Health, Precision Medicine, Big data and Analytics in India 
  • Current Offerings in the market

Theme and Key Topics

The theme of the conference will include topics such as:

  • Healthcare IT – Current scenario and outlook for 2018-20 
  • AI, Precision Medicine and Machine Learning – The future of service delivery 
  • Advanced and Predictive analytics – Transformational insights and Clinical Decision Making
  • Standards and interoperability – for Care Continuum
  • mHealth and Tele Medicine – Unlock the value of mobile and remote patient care 
  • Innovation and Startups – Smart Solutions to Perennial Problems
  • Home healthcare & IT – Making the right connection for better health


HIMSS is a global, cause-based, not-for- profit organization focused on better health through information technology (IT). HIMSS lead efforts to optimize health engagements and healthcare outcomes using IT. HIMSS is producing health IT thought leadership, education, events, market research and media services around the world. Founded in 1961, HIMSS encompasses more than 70,000 individuals, of which more than two-thirds work in healthcare provider, governmental and not-forprofit organizations across the globe, plus over 630 corporations and 450 not-forprofit partner organizations. 

 HIMSS, headquartered in Chicago, serves the global healthcare IT community with additional offices in USA, Europe and Asia. HIMSS India Chapter was formed in 2010 and has the distinction of being the first country-specific chapter of HIMSS outside USA. The Chapter has been at the forefront in forming Industry opinion and thought leadership on Healthcare IT challenges. With the revamped Board and Committees the Chapter has broadened its base forging alliances with representation from IT Industry, Hospital CIOs and SMEs

 Important Links: 
[1]: Conference Brochure: 
http://www.india.himsschapter.org/sites/himsschapter/files/HIMSS%20India%202018%20%20-%20Brochure%20-%20Ver1.2.pdf

 [2]: HIMSS India Conference 2018 Website: 
http://himssindiaconference.org/

 [3]: HIMSS India Chapter Website: 
http://www.india.himsschapter.org/

 [4]: Registration Form: 
https://docs.google.com/forms/d/e/1FAIpQLSf_NFlpj0rWggTKFIxoL_qbKYzCZ6_NrFFwqyTsv1J90rU2MQ/viewform?c=0&w=1

Author
Team HIMSS India

HIMSS India Conference and Exhibition 2018

Regulatory Essentials for e-Health in India by Dr. Milind Antani @milindantani

March 8, 2020 / #DIGITALHEALTH / 4 minutes of reading

A doctor should not give any advice over electronic media that would ordinarily require the physical examination of the patient.
» The Supreme Court has noted that prescriptions should generally not be given out without actual examination.
» It has also stated that prescriptions should not be given over the telephone, except in case of emergency.


 Ensure that your doctors/healthcare service providers are duly registered with the relevant state medical councils.
» Keep in mind that certain states require the doctor to be registered in the relevant state where the advice is being provided/patient is situated.

 Obtain informed consent from the patient before providing advice over telemedicine. Consent should have declarations that patient:
» has attained the legal age of majority;
» is voluntarily providing personal and medical information;
» has read the privacy policy, terms of use and other documentation;
» consents to the provider intimating public authorities about results and findings during the course of services, if required by law;
» understands the inherent risks related to the provision of telemedicine and other related services;
» is aware that s/he may withdraw consent at any time; and
» can inspect and modify personal information provided at any time.

 Make sure that the patient has read about the inherent limitations of telemedicine that arise due to absence of physical contact between the doctor and the patient.
» Ensure that the patient is aware that the issuance of a prescription is not guaranteed.

 Make it clear to the patient that telemedicine services are not for emergencies.
» Build in disclaimers that state that telemedicine services should not be used in case of an emergency.
» However, in case of one, please do not shy away from providing whatever assistance that you can.

 Ensure that no one other than the doctor is privy to the consultation, as it may result in breach of the patient’s privacy. Have a privacy policy in place. It should lay down:
» whose personal information is being collected;
» for what purpose;
» until when; and
» whether it will be disclosed/transferred to a third party or not.

 Have a terms of use of service in place and clearly identify:
» limitation of liability;
» indemnity; and
» the jurisdiction of courts.

 Bear in mind that e-prescriptions require digital signature of the doctor.
» A prescription carrying a picture of the doctor’s signature may not be a valid prescription.
» A scanned copy of a physical prescription may also not be considered valid.
 Maintain records of the consultation to the extent possible.
» The period of limitation for civil cases is 3 years. Maintaining records for this period at the minimum would help mitigate risk.
» The government is contemplating making it mandatory to maintain records of OPD patients.

 Always request patients to share contact information of a person who may be reached in case of an emergency during consultation. There are inherent limitations of operating a platform model versus a service model.
» In the platform model, the service provider cannot monitor quality beyond a point, else it will lose the status of a platform provider.
» In the service model, the quality can be monitored to a great extent. 

 However, there is a risk of litigation against the service provider for any deficiency in service rendered by the doctor.

 Documentation is key! Make sure you have all the required documents in place to mitigate risk.
» Proper documentation will help in clearly demarcating roles and responsibilities, which becomes essential in ascertaining liability.

 What are the changes you invisage in the legal framework governing Telemedicine services in india? 

 Dr. Milind Antani: I would consider e-Health more relevant than Telemedicine as e-Health has broader scope of activities. India has been witnessing significant upward surge in e-Health recently. However, regulations have not evolved completely or not matching the pace.

 However I am envisaging the following changes/new laws in near future

·       Electronic Healthcare Data Privacy legislation
·       E-Prescription guideline/ amendment to allow e-prescription
·       Amendment to allow e-Pharmacy
·       Telemedicine Act ( may not happen in near future but required)
·       Amendment in MCI Code to allow Audio Video consultation for doctors
·       Central license by MCI to practice in every state of India


The article has been authored by Dr. Milind Antani. 

Author
Dr. Milind Antani

Represents clients in matters including corporate mergers and acquisitions, investments, regulatory and transactional matters, intellectual property prosecution and litigation, joint ventures and formation of new companies. Focuses on Pharmaceutical, Life Sciences, Healthcare, Social Sector, Intellectual Property and Medical Devices

Glossary of Terms for Healthcare Data Analytics

March 8, 2020 / Uncategorized / 8 minutes of reading

BALANCED SCORECARD:
A framework developed by Robert Kaplan and David Norton that suggests four perspectives of performance measurement to provide a comprehensive view of an organisation. These are service user perspective, internal management perspective, continuous improvement perspective and financial perspective.


BENCHMARK:

A point of reference or standard by which something can be measured

BENCHMARKING:

The process of comparing the cost, cycle time, productivity, or quality of a specific process or method to another that is widely considered to be an industry standard or best practice.

CASEMIX:

Casemix is an internationally recognised system of measuring clinical activity incorporating the age, gender and health status of the population served by an organisation with a view to objective determination of hospital reimbursement.

DATA:

Data are numbers, symbols, words, images, graphics that have yet to be organised or analysed

DATA DICTIONARY:

A descriptive list of names (also called representations or displays), definitions, and attributes of data elements to be collected in an information system or database.

DATA ELEMENT:

A unit of data for which the definition, identification, representation, and permissible values are

DOMAINS OF QUALITY:

Are those definable, preferably measurable and actionable, attributes of the system that are related to its functioning to maintain, restore or improve health

DESCRIPTIVE ANALYTICS

As per gartner, Descriptive Analytics is the examination of data or content, usually manually performed, to answer the question “What happened?” (or What is happening?), characterized by traditional business intelligence (BI) and visualizations such as pie charts, bar charts, line graphs, tables, or generated narratives.

PREDICTIVE ANALYTICS

As per gartner, Predictive analytics describes any approach to data mining with four attributes:

1. An emphasis on prediction (rather than description, classification or clustering)
2. Rapid analysis measured in hours or days (rather than the stereotypical months of traditional data mining)
3. An emphasis on the business relevance of the resulting insights (no ivory tower analyses)

4. (increasingly) An emphasis on ease of use, thus making the tools accessible to business users.

PRESCRIPTIVE ANALYTICS

As per Gartner, Prescriptive Analytics is a form of advanced analytics which examines data or content to answer the question “What should be done?” or “What can we do to make _______ happen?”, and is characterized by techniques such as graph analysis, simulation, complex event processing, neural networks, recommendation engines, heuristics, and machine learning.

HEALTH INFORMATION:

Health Information is defined as information, recorded in any form or medium, which is created or communicated by an organisation or individual relating to the past, present or future, physical or mental health or social care of an individual or cohort. It also includes information relating to the management of the health and social care system

KPI SELECTION CRITERIA

KPIs should be chosen based on the judgement and consensus of experts and potential users. The List of characteristics and related questions which can be used to assist in the identification of KPIs. Adapted from criteria developed by the World Health Organization (WHO). 


Validity 
Does the KPI measure what it is supposed to measure? A valid KPI measures what it is supposed to measure and captures an important aspect of quality that can be influenced by the healthcare facility or system. Ideally KPIs selected should have links to processes and outcomes through scientific evidence. Measures that have been selected using scientific evidence possess high content validity and measures selected through consensus and guidelines will have high face validity. Content validity refers to whether the KPI captures important aspects of the quality of care provided. Face validity can be determined by the KPI making sense logically and clinically or from previous usage.

Reliability 
Does the KPI provide a consistent measure? The KPI should provide a consistent measure in the same population and settings irrespective of who performs the measurement. Reliability is similar to reproducibility to the extent that if the measure is repeated you should get the same result. Any variations in the result of the KPI should reflect actual changes in the process or outcome. Reliability can be influenced by training, the KPI definition and the precision of the data collection methods. Inter-rater reliability compares differences between evaluators performing the same measurement. Internal consistency examines the relationship between sub-indicators of the same overall measurement, and, if reliable, there should be correlation of the results. Test-retest reliability compares the difference between results when the same evaluator performs the measurement at different times. 

Explicit evidence base
Is the KPI supported by scientific evidence or the consensus of
experts? KPIs should be based on scientific evidence, the consensus of expert opinions among health professionals or on clinical guidelines. The preferred method of choosing KPIs is through evaluating scientific evidence in support of each KPI and rating the strength of that evidence. One example of a rating system is to give the highest rating to evidence (“A” evidence) from meta-analysis of randomised controlled trials and give a lesser rating (“B” evidence) to evidence for controlled studies without randomisation and a further lower rating (“C” evidence) to data from epidemiological studies. 
In healthcare, there may only be limited scientific evidence to support a KPI and it becomes Guidance on developing Key Performance Indicators and Minimum Data Sets to Monitor Healthcare Quality Health Information and Quality Authority 33 necessary to avail of expert opinion. There are a number of methods by which a KPI can be developed through facilitating group consensus from a panel of experts, such as the Delphi technique, the RAND appropriateness method and from clinical guidelines. Appendix 2 gives a brief description of each method and Appendix 3 provides an example of a Delphi assessment instrument. The expert panel can exist independently of the advisory group and are used as a point of reference for the KPI development process
Acceptability 
Are the KPIs acceptable? The data collected should be acceptable to those being assessed and to those carrying out the assessment. 
Feasibility 
Is it possible to collect the required data and is it worth the resources? There should be a feasibility analysis carried out to determine what data are currently collected and the resources required to collect any additional required data. The feasibility analysis should determine what data sources are currently available and if they are relevant to the needs of the current project. This will include determining if there are existing KPIs or benchmarking processes based on these data sources.

The reporting burden of collecting the data contained in the KPI should not outweigh the value of the information obtained. Preferably, data should be integrated into service delivery, and, where additional data are required that are not currently part of service delivery, there should be cost benefit analysis to determine if it is cost-effective to collect.

The feasibility analysis should also include what means are used to collect data and the limitations of the systems used for collection. It should also outline the reporting arrangements, including reporting arrangements for existing data collection and frequency of data collection and analyses.

Sensitivity 
Are small changes reflected in the results? Changes in the component of care being measured should be captured by the measurement process and reflected in the results. The performance indicator should be capable of detecting changes in the quality of care and these changes must be reflected in the resulting values. 

Specificity 
Does the KPI actually capture changes that occur in the service for
which the measure is intended? Only changes in the area being measured are reflected in the measurement results

Relevance 
What useful decisions can be made from the KPI? The results of the measurement should be of use in planning and the subsequent delivery of healthcare and contribute to performance improvement

Balance 
Do we have a set of KPIs that measure different aspects of the service? The final suite of indicators should measure different aspects of the service in order to provide a comprehensive picture of performance, including user perspective

Tested 

Have national and international KPIs been considered? There should be due consideration given to indicators that have been tried and tested in the national and international arena rather than developing new indicators for the same purpose.

Safe 
Will an undue focus on the KPI lead to potential adverse effects on other aspects of quality and safety? The indicator should not lead to an undue focus on the aspect of care being measured that may in turn lead to a compromise in the quality and safety of other aspects of the service.
Avoid duplication 
Has consideration been given to other projects or initiatives? Prior to developing the indicator due consideration should be given to other projects or initiatives to ensure that there will not be a duplication of data collection.

Timeliness
Is the information available within an acceptable period of time to inform decision-makers? The data should be available within a time period that enables decision-makers utilise the data to inform their decision-making process. If the data is required for operational purposes, then it will be required within a shorter timeframe than data used for long term strategic purposes. 

METADATA:

Data that defines and describes other data

MINIMUM DATA SET:

The minimum set of data elements that are required to be collected for a specific purpose

NUMERATOR:

The specifications that define the subset of data items in the denominator that meet the indicator criteria.

KEY PERFORMANCE INDICATORS:

Performance Indicators are specific and measurable elements of practice that can be used to assess quality of care. Indicators are quantitative measures of structures, processes or outcomes that may be correlated with the quality of care delivered by the healthcare system. 

PROCESS INDICATORS:

Performance indicators that monitor the activities carried out in the assessment/diagnosis and treatment of service users.

OUTCOME INDICATORS:

Performance indicators that monitor the desired states resulting from care processes, which may include reduction in morbidity and mortality, and improvement in the quality of life.

RELIABILITY:

Reliability is the consistency of your measurement, or the degree to which an instrument measures the same way each time it is used under the same condition with the same subjects.

STRUCTURE INDICATORS:

Performance indicators that monitor the attributes of the health system that contribute to its ability to meet the healthcare needs of the population.

The Delphi Technique:

The Delphi technique is a facilitated structured process whereby a panel of experts complete questionnaires (see Appendix 3 for example) remotely and, through feedback and scoring over a number of rounds where some KPIs are discarded, a consensus is achieved on a final set of KPIs. The panel need not ever meet face-to-face and each individual’s feedback is provided anonymously to the panel, which eliminates the possibility of undue influence by dominant personalities within the panel.

The RAND appropriateness method:

The RAND appropriateness method combines scientific evidence with expert
opinion by facilitating experts to rate, discuss and re-rate KPIs. Unlike the Delphi technique the expert panel meet face-to-face to discuss possible KPIs and are given a copy of the scientific literature in support of the KPIs so that they can ground their opinion on evidence-based literature

VALIDITY:

Validity of indicators refers to whether performance indicators are measuring what they are supposed to measure. e are constantly looking for Healthcare Informatics & Digital Health Experts to share their experiences by writing articles on Technology benefiting in the delivery of Healthcare Services.

And there you go, its fairly simple and we look forward to you sharing your experiences with our community of readers. We appreciate you considering sharing your knowledge via The HCITExpert Blog
Author
Team HCITExperts

Your partner in Digital Health Transformation using innovative and insightful ideas

Glossary of Terms & Acronyms for Artificial Intelligence and Machine Learning

March 28, 2020 / AI/ML/DL / 7 minutes of reading

AI & Machine Learning Terms

Artificial intelligence The development of computers capable of tasks that typically require human intelligence. A machine’s ability to make decisions and perform tasks that simulate human intelligence and behavior.

Machine learning Using example data or experience to refine how computers make predictions or perform a task. A facet of AI that focuses on algorithms, allowing machines to learn without being programmed and change when exposed to new data.   

Deep learning A machine learning technique in which data is filtered through self-adjusting networks of math loosely inspired by neurons in the brain. The ability for machines to autonomously mimic human thought patterns through artificial neural networks composed of cascading layers of information.  

Supervised learning Showing software labeled example data, such as photographs, to teach a computer what to do. A type of machine learning in which output datasets train the machine to generate the desired algorithms, like a teacher supervising a student; more common than unsupervised learning.  

Unsupervised learning Learning without annotated examples, just from experience of data or the world—trivial for humans but not generally practical for machines. Yet. A type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses. The most common unsupervised learning method is cluster analysis.  

Reinforcement learning Software that experiments with different actions to figure out how to maximize a virtual reward, such as scoring points in a game.  

Artificial general intelligence   As yet nonexistent software that displays a humanlike ability to adapt to different environments and tasks, and transfer knowledge between them.

Large-scale Machine Learning Design of learning algorithms, as well as scaling existing algorithms, to work with extremely large data sets.

Deep Learning Model composed of inputs such as image or audio and several hidden layers of sub-models that serve as input for the next layer and ultimately an output or activation function.

Natural Language Processing (NLP) Algorithms that process human language input and convert it into understandable representations. The ability for a program to recognize human communication as it is meant to be understood. 

Collaborative Systems Models and algorithms to help develop autonomous systems that can work collaboratively with other systems and with humans.

Computer Vision (Image Analytics) The process of pulling relevant information from an image or sets of images for advanced classification and analysis.

Algorithmic Game Theory and Computational Social Choice Systems that address the economic and social computing dimensions of AI, such as how systems can handle potentially misaligned incentives, including self-interested human participants or firms and the automated AI-based agents representing them.

Soft Robotics (Robotic Process Automation – RPA) Automation of repetitive tasks and common processes such as IT, customer servicing and sales without the need to transform existing IT system maps.

Algorithms: A set of rules or instructions given to an AI, neural network, or other machines to help it learn on its own; classification, clustering, recommendation, and regression are four of the most popular types.

Artificial neural network (ANN): A learning model created to act like a human brain that solves tasks that are too difficult for traditional computer systems to solve.

Autonomic computing: A system’s capacity for adaptive self-management of its own resources for high-level computing functions without user input.

Chatbots: A chat robot (chatbot for short) that is designed to simulate a conversation with human users by communicating through text chats, voice commands, or both. They are a commonly used interface for computer programs that include AI capabilities.

Classification: Classification algorithms let machines assign a category to a data point based on training data.

Cluster analysis: A type of unsupervised learning used for exploratory data analysis to find hidden patterns or grouping in data; clusters are modeled with a measure of similarity defined by metrics such as Euclidean or probabilistic distance.

Clustering: Clustering algorithms let machines group data points or items into groups with similar characteristics.

Cognitive computing: A computerized model that mimics the way the human brain thinks. It involves self-learning through the use of data mining, natural language processing, and pattern recognition.

Convolutional neural network (CNN): A type of neural networks that identifies and makes sense of images.

Data mining: The examination of data sets to discover and mine patterns from that data that can be of further use.

Data science: An interdisciplinary field that combines scientific methods, systems, and processes from statistics, information science, and computer science to provide insight into phenomenon via either structured or unstructured data.

Decision tree: A tree and branch-based model used to map decisions and their possible consequences, similar to a flow chart.

Fluent: A type of condition that can change over time.

Game AI: A form of AI specific to gaming that uses an algorithm to replace randomness. It is a computational behavior used in non-player characters to generate human-like intelligence and reaction-based actions taken by the player.

Genetic algorithm: An evolutionary algorithm based on principles of genetics and natural selection that is used to find optimal or near-optimal solutions to difficult problems that would otherwise take decades to solve.

Heuristic search techniques: Support that narrows down the search for optimal solutions for a problem by eliminating options that are incorrect.

Knowledge engineering: Focuses on building knowledge-based systems, including all of the scientific, technical, and social aspects of it.

Logic programming: A type of programming paradigm in which computation is carried out based on the knowledge repository of facts and rules; LISP and Prolog are two logic programming languages used for AI programming.

Machine intelligence: An umbrella term that encompasses machine learning, deep learning, and classical learning algorithms.

Machine perception: The ability for a system to receive and interpret data from the outside world similarly to how humans use our senses. This is typically done with attached hardware, though software is also usable.

Recurrent neural network (RNN): A type of neural network that makes sense of sequential information and recognizes patterns, and creates outputs based on those calculations.

Swarm behavior: From the perspective of the mathematical modeler, it is an emergent behavior arising from simple rules that are followed by individuals and does not involve any central coordination.

TerminologyDefinition
Automated communicationsAlso known as an interactive agent, or artificial conversational entity, these are computer programs which conduct a conversation via auditory or textual methods. For example, chatbots, mailbots.
Automated data analystAI solutions aimed at performing the job of data analysts and data scientists and bridging the gap between such roles and business imperatives. For example, these might include programs that are able to develop a deep understanding of customer preferences from data, identify high-risk customer groups and tailor interaction touch points in a manner personalised to such customers.
Automated operational and efficiency analystAI solutions targeted at increasing operational efficiency and reducing costs. These include AI programs and bots aimed at automating repetitive manual tasks such as identifying and correcting data and formatting mistakes, performing back office tasks and automating repetitive interactions with customers.
Automated research and information aggregationApplications of AI that involve aggregating and processing large volumes of information on a topic so as to generate meaningful insights. For example, aggregating information from research papers or medical journals for diagnosis support, identifying online hoax, bad reporting and statistics, and identifying plagiarised publications.
Automated sales analystAI-powered digital analysts for sales and marketing decisions. These programs are able to test a range of scenarios using internal and external data to predict the impact of marketing strategies such as promotions and campaigns, simulate ‘what if’ scenarios against multiple hypotheses and perform root cause analyses against business results.
Business decision makers/influencersA sub-set of participants in the survey who have identified themselves to be either in a decision making role or an influencing role in their current organisations. Some of the survey questions had been specifically targeted towards this group.
Decision support systemsDecision support systems (DSS) are a specific class of computerised information systems that support business and organisational decision-making activities.
Machine learningMachine learning is concerned with computer programs that automatically improve their performance through experience.
Predictive analyticsPredictive analytics is an area of statistics that deals with extracting information from data and using it to predict trends and behaviour patterns–for example, sales forecasts, predicting customer churn and industrial
machine failure.
RoboticsRobotics deals with the design, construction, operation and use of robots, as well as computer systems for their control, sensory feedback and information processing. Environmental information such as imagery and sound are captured using a group of sensors and the same are processed using various computerised techniques for the robot to respond.
Virtual personal assistantsVirtual assistants use natural language processing (NLP) to match user text or voice input to executable commands. Many continually learn using AI techniques, including machine learning. For example, Apple’s Siri, Amazon’s Alexa, Google Now.
AI advisorsAI advisors are machines or systems that monitor employees’ progress and performance. They are responsible for the growth of the employee in the organisation and for the delivery of projects.
AI assistantsAI assistants are machines or systems or application programming interfaces ([APIs] a set of subroutine definitions, protocols and tools for building application software) that perform non-value adding services such as scheduling and email management.

Source: https://www.pwc.in/assets/pdfs/consulting/technology/data-and-analytics/artificial-intelligence-in-india-hype-or-reality/artificial-intelligence-in-india-hype-or-reality.pdf

References


[1]: pwc AI: https://www.pwc.com/ai

[2]: AI: The Complete Guide: 
https://www.wired.com/story/guide-artificial-intelligence/
[3]: https://dzone.com/articles/ai-glossary

Glossary of Healthcare & HealthIT Terms and Acronyms

March 28, 2020 / Uncategorized / 14 minutes of reading


ACO (Accountable Care Organization) MEDICARE’s outcomes-based contracting approach

 Activity Diagram A UML Diagram that shows a workflow process, particularly focused on communication and the actors involved in that communication. Introduced as part of the HDF as part of the requirements analysis for HL7 standrads.

ADT – Admissions, Discharge & Transfer

 ANSI American National Standards Institute. Founded in 1918, ANSI itself does not develop standards. ANSI’s roles include serving as the coordinator for U.S. voluntary standards efforts, acting as the approval body to recognize documents developed by other national organizations as American National Standards, acting as the U.S. representative in international and regional standards efforts, and serving as a clearinghouse for national and international standards development information.

 Attribute Type The last part of an attribute name (suffix). Attribute type suffixes are rough classifiers for the meaning of the attribute. See also Data Type for contrast.

 Authenticated Document A status in which a document or entry has been signed manually or electronically by one or more individuals who attest to its accuracy. No explicit determination is made that the assigned individual has performed the authentication. While the standard allows multiple instances of authentication, it would be typical to have a single instance of authentication, usually by the assigned individual.

 Auxiliary Application An auxiliary application neither exerts control over, nor requests changes to a schedule. It is only concerned with gathering information about a particular schedule. It can be considered an “interested third- party,” in that it is interested in any changes to a particular schedule, but has no interest in changing it or controlling it in any way. It may gather information passively or actively. An auxiliary application passively collects information by receiving unsolicited updates from a filler application.

Arden Syntax an approach to specifying medical knowledge and clinical decision support rules in a form that is independent of any EHR and thus sharable across hospitals

ARRA (American Recovery and Reconstruction Act) the Obama administration’s 2009 economic stimulus bill

Blue Button an ASCII text based standard for heath information sharing first introduced by the Veteran’s Administration to facilitate access to records stored in VistA by their patients. The newer Blue Button + format provides both human and machine readable formats.

Bio-sensing wearables

A biosensor is an analytical device which converts a biological response into an electrical signal and wearables are on or in body accessories that enhance user experience. Biosensing wearables can monitor changes in physiology and the external environment. They are easy to use and provide useful, real-time information by allowing continuous physiological monitoring in a wide range of wearable forms.

 CCD (Continuity of Care Document) an XML-based patient summary based on the CDA architecture

CCOW (Clinical Context Object Workshop) an HL7 standard for synchronizing and coordinating applications to automatically follow the patient, user (and other) contexts to allow the clinical user’s experience to resemble interacting with a single system, when they are using multiple, independent applications from many different systems

CCR (Continuity of Care Record) an XML-based patient summary format that preceded CDA

CCDA (Consolidated Clinical Document Architecture) the second revision of HL7’s CDA architecture that attempts to introduce more standard templates to facilitate information sharing (a mandate of Meaningful Use 2)

 CDA (Clinical Document Architecture) an XML-based markup standard intended to specify the encoding, structure and semantics of clinical documents

CDC (Centers for Disease Control and Prevention) the federal agency focused on disease in the community.

 CA (Certificate Authority) an entity that digitally signs certificate requests and issues X.509 digital certificates that link a public key to attributes of its owner

CIMI (Clinical Information Modeling Initiative) an independent collaboration of major health providers improve the interoperability of healthcare information systems through shared and implementable clinical information models

CMS (Centers for Medicare & Medicaid Services) the component of the Department of Health and Human Services that administers the Medicare and Medicaid programs

CommonWell Alliance a group of major health IT companies that is working to achieve interoperability among their respective software products and services

Complete EHR an EHR software product that, by itself, is capable of meeting the requirements of certification and Meaningful Use

CONNECT ONC supported open source software for managing the centralized model of health information exchange

 CPT (Current Procedural Terminology) the American Medical Association’s standard for coding medical procedures

 De-identified Patient Health Information PHI from which all data elements that could allow the data to be traced back to the patient have been removed

 DIRECT a set of ONC supported standards for secure exchange of health information using email

 DNS (Domain Name System) the naming system for computers, services, or any resource connected to the Internet (or a private network). Among other things, it translates domain names (e.g. eBay.com) to the numerical IP addresses needed to locate Internet connected resources.

eHealth
The transfer of health resources and healthcare by electronic means, encompassing three main areas:
• the delivery of health information, for health professionals and health consumers, through the Internet and telecommunications
•  using the power of IT and e-commerce to improve public health services, e.g. through the education and training of health workers
•  the use of e-commerce and e-business practices in health systems management

Electronic health records (EHR)
A set of records that clinicians control to co-ordinate their team work within and between healthcare teams.

Electronic patient health records (EPR)
A set of records that the patient controls and which allows the patient to work with their clinical team across institutional boundaries.

EDI/X12 a format for electronic messaging that utilizes cryptic but compact notation primarily to support computer-to-computer commercial information exchange

eHealth Exchange a set of standards, services and policies that enable secure nationwide, Internet-based health information exchange using CONNECT or one of the commercial HIE products that support eHealth Exchange

EHR (Electronic Health Record) a stakeholder wide electronic record of a patient’s complete health situation

EHR Certification a set of technical requirements developed by ONC that, if met, quality an EHR to be used by an Eligible Professional to achieve Meaningful Use

Eligible Professionals (Medicaid) health providers who are eligible for Medicaid Meaningful Use payments: doctors of medicine, osteopathy, dental surgery, dental medicine, nurse practitioners, nurse certified nurse-midwifes, and physician assistants who working in a Federally Qualified Health Center or Rural Health Clinic that is led by a physician assistant

 Eligible Professionals (Medicare) health providers who are eligible for Medicare Meaningful Use payments: doctors of medicine, osteopathy, dental surgery, dental medicine, podiatry, optometry and chiropractic

 EMPI an enterprise master patient index

EMR (Electronic Medical Record) an electronic record used by a licensed professional care provider

GELLO a programming language intended for use as a standard query and expression language for clinical decision support. Now compatible with the HL7 version 3.0 Reference Information Model (RIM).

HDF (HL7 Development Framework) the framework used by HL7 to produce specifications for data, messaging process and other standards

Health System a network of providers that are affiliated for the more integrated delivery of care

Healtheway an ONC supported public-private partnership to promote nationwide health information exchange via the eHealth Exchange

HIE (Health Information Exchange) the sharing of digital health information by the various stakeholders involved, including the patient

 HIMSS (Healthcare Information and Management Systems Society) describes itself as a “a global, cause-based, not-for-profit organization focused on better health through information technology (IT)”

HIPAA (Health Insurance Portability and Accountability Act of 1996) legislation intended to secure health insurance for employees changing jobs and simplify administration with electronic transactions. It also defines the rules concerning patient privacy and security for PHI

HISP (Health ISP) a component of Direct that provides a provider directory, secure email addresses and public-key infrastructure (PKI)

HIT (Health Information Technology) the set of tools needed to facilitate electronic documentation and management of healthcare delivery

HITSP (Healthcare Information Technology Standards Panel) a public/private partnership to promote interoperability through standards

HL7 (Health Level 7) a not-for-profit global organization to establish standards for interoperability

HMO (Health Maintenance Organization) an organization that provides managed healthcare on a prepaid basis. Employers with 25 or more employees must offer federally certified HMO options if they offer traditional healthcare options

hQuery an ONC funded, open source effort to develop a generalized set of distributed queries across diverse EHRs for purposes such as clinical research

HTTP (Hypertext Transfer Protocol) a query-response protocol used to transfer information between web browsers and connected servers. HTTPS is the secure version.

ICD (International Classification of Disease) the World Health Organization’s almost universally used standard codes for diagnoses. The current version is ICD-10 and it was adopted in the US on October 1, 2015 — well after most other advanced countries had moved to it.

 IHTSDO (International Health Terminology Standard Development Organisation) the multinational organization that maintains SNOMED

 IHIP Integrated Health Information Platform. An Integrated Health Information Platform (IHIP) is being setup by the Ministry of Health and Family Welfare (MoHFW). The primary objective of IHIP is to enable the creation of standards compliant Electronic Health Records (EHRs) of the citizens on a pan-India basis along with the integration and interoperability of the EHRs through a comprehensive Health Information Exchange (HIE) as part of this centralized accessible platform.

IP Address a 32 bit (the standard is changing to 128 bit to accommodate Internet growth) number assigned to each device in an Internet Protocol network and that indicates where it is in that network.

I2b2 (Informatics for Integrating Biology and the Bedside) a scalable query framework for exploration of clinical and genomic data for research to design targeted therapies for individual patients with diseases having genetic origins

Interoperability the ability of diverse information systems to seamlessly share data and coordinate on tasks involving multiple systems.

LDAP (Lightweight Directory Access Protocol) is a protocol for accessing (including searching) and maintaining distributed directory information services (such as an email directory) over an IP network.

LOINC (Logical Observation Identifiers Names and Codes) the Regenstrief Institute’s standard for laboratory and clinical observations

Meaningful Use a set of usage requirements defined in three stages by ONC under which eligible professionals are paid for adopting a certified EHR

MedDRA (Medical Dictionary for Regulatory Activities) the International Conference on Harmonisation’s classification of adverse event information associated with the use of biopharmaceuticals and other medical products

Medicaid the joint federal/state program to provide healthcare services to poor and some disabled US citizens

Medicare the federally operated program to provide healthcare services to US citizens over the age of 65

MIME (Multipurpose Internet Mail Extensions) the Internet standard for the format of email attachments used in Direct. S/MIME is the secure version.

MLM (Medical Logic Module) the basic unit in the Arden Syntax that contains sufficient medical knowledge and rules to make one clinical decision.

Modular EHR a software component that delivers at least one of the key services required of a Certified EHR

 Moodle (Modular Object-Oriented Dynamic Learning Environment) is one of the most popular open source Course Management Systems (CMS). It is written in PHP programming language and distributed under the GNU General Public License. Moodle was created by Martin Dougiama to help educators to create online courses with a focus on interaction and collaborative construction of content, and it is in continual evolution.

Mobile health (mHealth)
Medical and public health practice supported by mobile devices (mobile phones, smart phones and tablets), patient monitoring devices, personal digital assistants (PDAs), and other wireless devices. Utilising a mobile phone’s core voice and short messaging service (SMS) and more complex functionalities and applications including general packet radio service (GPRS), third and fourth generation mobile telecommunications (3G and 4G systems), global positioning system (GPS), and Bluetooth technology.

Mobile applications (apps)
A software application that can run on a mobile platform (i.e. a handheld commercial off-theshelf computing platform, with or without wireless connectivity) or a web-based software application that is tailored to a mobile platform but is executed on a server.

 MPI (Master Patient Index) software to provide correct matching of patients across multiple software systems, typically within a health enterprise

MUMPS (Massachusetts General Utility Multi-Programming System) an integrated programming language and file management system designed in the late 1960’s for medical data processing that is the basis for some of the most widely installed enterprise health information systems

NDC (National Drug Codes) the Food and Drug Administration’s numbering system for all medications commercially available in the US

ONC (Office of the National Coordinator for Health Information Technology) the agency created in 2004 within the Department of Health and Human Services to promote the deployment of HIT in the US

Online patient communities

Online discussion groups allowing patients to learn from peers and professionals including how to understand their own data. They provide access to relevant, timely information and support others with similar conditions.

Outcomes-based Contract an approach to pay for healthcare that rewards physician performance against certain defined quality metrics when combined with a lower than predicted cost of care

Participatory medicine
Patients and clinicians work together to improve the patient’s health – in which patients have equal access to all data, are case managers of their own illness and co-producers of their own health. Primary care professionals become gateways not gatekeepers.

Patient portal
A website that gives patients access to the data and information in their electronic health record. Can also be used to book appointments and order repeat prescriptions.

Personal health records (PHRs)

A set of records that the patient controls and enables users to see who wrote what when and what for.

P4P (Pay for Performance) an approach to pay for healthcare that rewards physician performance against certain defined quality metrics

PCMH (Patient-Centered Medical Home) a team based healthcare delivery model often particularly focused on the management of chronic disease

PCP (Primary Care Physician) the generalist in a patient’s care team who assumes overall responsibility for all their health issues and often the gatekeeper who must generate referrals to specialists

PHI (Protected Health Information) any health or health related information that can be related back to a specific patient. PHI is subject to HIPAA regulations.

PKI (Public Key Infrastructure) a widely used system for protection of documents, messages and other data that rests on a pair of public and private keys to allow for a variety of use cases

Private Key the protected (known only to its owner) part of the special pair of numbers used to encrypt documents using PKI

Provider health professionals including physicians, nurse practitioners, physicians’ assistants that are engaged in direct patient care

Public Key the public part of the special pair of numbers used to encrypt documents using PKI

RA (Registration Authority) an entity that collects information for the purpose of verifying the identity of an individual or organization and produces a certificate request

Synthetic Health Data facsimile clinical data created by a software system to realistically resemble actual patient data

 Templates (CDA) the reusable basic XML-based building blocks of a CDA document that can represent the entire document, its sections or the data entries within a section

Read Codes a hierarchical clinical terminology system used in General Practice in the United Kingdom

Resource Description Framework (RDF) a method for describing or modeling of information on the web using subject-predicate-object expressions (triples) in the form of subject-predicate-object expressions that could be used to represent health ontologies (SNOMED, ICD-1)

RIM (Reference Information Model) a pictorial representation of the HL7 clinical data (domains) that illustrates the life cycle of an HL7 message or groups of related messages

Semantic web the proposed next generation of web in which technologies like RDF would create a “web of data” in which browsers (and other tools) could “understand” the content of web pages

SMTP (Simplified Mail Transport Protocol) the Internet standard for email used by Direct. The secure version is S/SMTP

SNOMED (Standard Nomenclature of Medicine) a comprehensive, hierarchical healthcare terminology system.

SNOMED CT (Standard Nomenclature of Medicine) SNOMED subset for the electronic health record. SNOMED CT: Is the most comprehensive, multilingual clinical healthcare terminology in the world. Is a resource with comprehensive, scientifically validated clinical content. Enables consistent, processable representation of clinical content in electronic health records. Is mapped to other international standards.  Is already used in more than fifty countries

When implemented in software applications, SNOMED CT can be used to represent clinically relevant information consistently, reliably and comprehensively as an integral part of producing electronic health information.

Technology enabled Care (TEC)
The use of technology to enhance the quality and cost-effectiveness of care and support and improve outcomes for individuals through the application of technology (including, but not limited to, the use of telecare, telehealth, and mobile health and wellbeing) as an integral part of the care and support process.

Telecare
The continuous, automatic and remote monitoring of activity/lifestyle changes over time, providing real time alerts or calls for help in emergencies and helping to manage the risks associated with independent living, enabling people to live independently for longer, particularly those who require a combination of health and social care.

Telehealth and Telehealth
Telehealth involves the consistent and accurate remote monitoring and management of a health condition including vital signs monitoring. It involves the exchange of information between patient and HCPs to identify trends or changes in the patient’s condition, helping to avoid hospital admissions, support early discharge and improve self-care. Telehealth helps educate, train and support people to self-care.

Telemedicine

Telemedicine uses telecommunication and electronic information technologies to provide clinical healthcare at a distance, improving access to medical services and specialists. It permits communications between patient and medical staff as well the transmission of medical, imaging and health informatics data from one site to another. New forms of telemedicine include videotelephony, advanced diagnostics and telemedical devices to support home care.

ToC (Transition of Care Initiative) the effort to develop a standard electronic clinical summary for transitions of care from one venue to another

TPO HIPAA exception for providers, insurance companies and other health-care entities to exchange information necessary for Treatment, Payment or Operations of healthcare businesses

VDT (View, Download, Transmit) a requirement of Meaningful Use Stage 2 that patients view, download or transmit their health information

VistA (Veterans Health Information Systems and Technology Architecture) the Veteran’s Administration’s system wide, MUMPS based health information infrastructure

X.509 digital certificate the technical name for an electronic document issued by a CA that uses a digital signature to bind a public key with an identity based on information from an RA

XDR (External Data Representation) an operating system and transport method agnostic mechanism for exchanging data that is encoded/decoded into/from the XDR format.

XDM (IHE Cross Enterprise Document Media Interchange) a standard mechanism for including both documents and meta-data in zip format using agreed upon conventions for directory structure and location of files.

XDS (Cross-Enterprise Document Sharing) the use of federated document repositories and a document registry to create a longitudinal record of information about a patient

XML (Xtensible Markup Language) a widely used standard for machine and human readable electronic documents and the language used to define CDA templates

 XMPI a cross organizational master patient index capable of dealing with many unaffiliated hospitals and health systems

LMIS – laboratory information management system

RIS – Radiology Information System

PACS – Picture Archival and Communications System 

DICOM – Digital Imaging and Communications in Medicine


References

 [1]: Glossary of Terms on HL7: 
https://www.hl7.org/documentcenter/public/calendarofevents/FirstTime/Glossary%20of%20terms.pdf

[2]: HEALTH INFORMATICS ON FHIR: https://www.coursera.org/learn/fhir

 [3]: pwc AI: https://www.pwc.com/ai

[4]: Connected health: How digital technology is transforming health and social care: 
https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences-health-care/deloitte-uk-connected-health.pdf

Artificial Intelligence #AI Could Add $957 Billion to Indian Economy, According to New Research by @AccentureIndia

March 8, 2020 / AI/ML/DL / 3 minutes of reading

In a recently published report by Accenture, they have highlighted the need for india to invest in AI, we bring you the excerpts of the report. (The following content is sourced from the Accenture report).
Artificial intelligence (AI) has reached a tipping point. The combination of the technology, data and talent that make intelligent systems possible has reached critical mass, driving extraordinary growth in AI investment. Across the world, G20 countries have been building up their AI capabilities. The power of AI starts with people and intelligent technologies working together within and across company boundaries to create better outcomes for customers and society. But India is not fully prepared to seize the enormous opportunities that AI presents. Even with a tech-savvy talent pool, renowned universities, healthy levels of entrepreneurship and strong corporations, the country lags on key indicators of AI development. Much work remains. 


The report, ‘Rewire for Growth,’ estimates that AI has the potential to increase India’s annual growth rate of gross value added (GVA) by 1.3 percentage points, lifting the country’s income by 15 percent in 2035. To avoid missing out on this opportunity, policy makers and business leaders must prepare for, and work toward, the AI revolution. 


The era of AI has arrived. Established companies are moving far beyond experimentation. Money is flowing into AI technologies and applications at large companies. The number of patents filed on AI technologies in G20 countries has increased at a more than 26 percent compound annual growth rate since 2010. Funding for AI startups has been growing at a compound annual growth rate of almost 60 percent.

AI is a new factor of production that can augment labor productivity and innovation while driving growth in at least three important ways:

Mobilize Intelligent Automation
Automate complex, physicalworld tasks that require adaptability and agility.

Empower Existing Workforces
Complement and enhance the skills and abilities of workforces.

Drive Innovations
Let AI be a catalyst for broad structural transformation of the economy. Do things differently, do different things.


The report points out AI is expected to raise India’s annual growth rate by 1.3 percentage points—in a scenario of intelligent machines and humans working together to solve the country’s most difficult problems in 2035

AI TENDING TO INDIA’S HEALTH
India’s healthcare providers have embraced artificial intelligence, recognizing its significant value in better diagnostics with data intelligence and in improving patient experience with AI-powered solutions.

Take Manipal Hospitals, headquartered in Bengaluru, which is using IBM Watson for Oncology, a cognitive-computing platform, to help physicians identify personalized cancer care options across the country.

In cardiac care, Columbia Asia Hospitals in Bengaluru is using startup Cardiotrack’s AI algorithms to predict and diagnose cardiac diseases, disorders, and ailments.

And in eye care, Aravind Eye Hospital is working with Google to use AI in ophthalmology for diabetic retinopathy screening. Also, the government of Telangana is planning to use Microsoft Intelligent Network for Eyecare (MINE), an AI platform, to reduce avoidable blindness, which would make it the first state in India to deploy AI for eye care screening as part of the Rashtriya Bal Swasthya Karyakram program under the National Health Mission.

Accenture, for its part, has developed an AI-powered smartphone solution to help the visually impaired improve the way they experience the world around them and enhance their productivity in the workplace. The solution, called
Drishti, was initially developed and tested through a collaboration with the National Association for the Blind in India.


AI has the potential to have a broad-based disruptive impact on society, creating a variety of economic benefits. While some of these benefits can be measured, others, such as consumer convenience and time savings, are far more intangible in nature. Our analysis focuses on measuring the GVA impact of AI.

Read the press release here >> 
https://newsroom.accenture.com/news/artificial-intelligence-could-add-957-billion-to-indian-economy-according-to-new-research-by-accenture.htm

Read the complete report here >> 
https://www.accenture.com/in-en/insight-ai-economic-growth-india

Author
Team HCITExperts

Your partner in Digital Health Transformation using innovative and insightful ideas

Streamlining New Horizons of Technology in Healthcare by @exploreevents1

March 8, 2020 / CONFERENCES / 2 minutes of reading

About the event

In its 2nd year the Smart Tech Healthcare is one among the most dedicated conferences aimed at streamlining new horizons of technology in healthcare which provides a common platform for the industry and other stakeholders to come together to discuss the key challenges, learn from the best practices adopted across the country and ensure their firm is positioned to comply with digital health trends in the evolving industry. Today, our health care system has changed dramatically but it’s still too difficult for families in rural India to find quality, affordable health care.

 The consumer health technologies — apps, telemedicine, wearables, self-diagnosis tools — which has the potential to strengthen the patient-physician connection and improve health outcomes in all sorts of technology-enabled ways, that’s the opportunity to learn, discuss the new trends in this summit.

 With the success of the first annual Smart Tech Healthcare focused of redefining healthcare with IT & more than 250 attendees, 45 speakers, 9 supporting associations. The event is projected to be big with more than 350 attendees will be the most diverse gathering of public sector, health and technology industry leaders working at the intersection of innovative product and service development, research, business and policy throughout the world. Building thought leadership across the ecosystem, this year’s conference focuses on an increasingly business & consumer oriented, technology-enabled and collaborative approach to improving digital health.

Key Topics:

Here are the topics of discussion: 
* Storytelling in a Digital Age: Transforming healthcare 2030 with IT 
* Blockchain as an enabler of countrywide interoperability 
* Redesigning Healthcare: the future of Artificial Intelligence & Robotics 
* The future for Technology Enabled Care: How the industry realises the opportunities 
* Revolutionising the Internet of Health & Medical Things 
* Interoperability in the Post-EHR era 
* Payer-Provider Collaboration on Data: The Leading Edge. 
* In-depth analysis of today’s megatrends (VR, tele-everything, Robotics, wearables, digital therapies). 
* Deeper Dive: Understanding the Emerging Threats. 
* Population Health Strategies: Improved outcomes and care coordination.

Event Themes: 

Health Informatics, Telehealth, Business Intelligence, AI & Robotics, EHRS, Interoperability, Data Integration, Entrepreneurship & Venture Investment, Cyber Security, IOHT, Blockchain, Transforming healthcare, Artificial Intelligence, Big Data 

Who should Attend?

  • Hospital CEOs
  • Hospital Management Company Senior Management
  • Health Care Policy Personnel
  • Representatives of Hospital Supplier / Manufacturer / Distributor Companies
  • Vice Presidents of Sales and/or Marketing
  • Health Care Managers
  • Health Industry Analysts / Consultants

Why attend?

  • Learn about future healthcare technology
  • Hear from the leaders of healthcare  industry addressing future health care trends
  • Network with senior executives from hospital management companies and hospitals

 Register 


HCITExpert Blog is proud to be associated as a media partner for the event >>
http://www.exploreexhibitions.com/healthcare/index.php/partner/media-parters


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Streamlining New Horizons of Technology in Healthcare by @exploreevents1


A collection of Potential Usecases for #Blockchain in Healthcare

March 8, 2020 / BLOCKCHAIN / 15 minutes of reading
Every once in a while a new technology finds its way in the Gartner Hype Cycle for Technologies (in Healthcare) and its effectiveness and usability is applied to the management and interoperability of Healthcare Records. For instance, access to the Healthcare records by various stakeholders in the care continuum: care providers and patients. 



Gartner in their recent report defines Blockchain as a Digital Platform. And healthcare industry has been perennially on the lookout for a Digital Platform that will allow for an efficient and secure way to share patient data. Providing access to the healthcare data involves providing access to the patient data to relevant stakeholders at the right time and to the right person, not only ensuring the privacy but also providing the patient control of their data. 

 Another problem that remains evasive in healthcare is driven by privacy of the patient data, and has been at times been seen to be impeding the flow of patient data between disparate systems, (i.e., Interoperability). 

 We now have the Blockchain Technology and various companies are working to apply the technology to help solve not only the interoperability problem but also applying the same technology to solve various usecases in the Care Continuum, to save costs, improve efficiency, ensure privacy.

 So what are the problems Blockchain is being applied to in the Healthcare context? What are the benefits one would accrue by applying Blockchain to Healthcare and what are the pitfalls.

 The past august, ONC in the US setout a Blockchain challenge with the objective, 

“The goal of this Ideation Challenge is to solicit White Papers that investigate the relationship between Blockchain technology and its use in Health IT and/or health-related research. The paper should discuss the cryptography and underlying fundamentals of Blockchain technology, examine how the use of Blockchain can advance industry interoperability needs expressed in the Office of the National Coordinator for Health Information Technology’s (ONC) Shared Nationwide Interoperability Roadmap, as well as for Patient Centered Outcomes Research (PCOR), the Precision Medicine Initiative (PMI), delivery system reform, and other healthcare delivery needs, as well as provide recommendations for Blockchain’s implementation. In addition to a monetary award, winners may also have the opportunity to present their White Papers at an industry-wide “Blockchain & Healthcare Workshop” co- hosted by ONC and NIST.”

As part of the Ideation Challenge, the following papers were the declared winners:

 1. Blockchain and Health IT: Algorithms, Privacy, and Data: This papers discusses the need to create a peer-to- peer network that enables parties to jointly store and analyze data with complete privacy, based on highly optimized version of multi-party computation with a secret-sharing. An auditable, tamper-proof distributed ledger (a permissioned blockchain) records and controls access through smart contracts and digital identities. We conclude with an initial use case of OPAL/Enigma that could empower precision medicine clinical trials and research. 
Authors:  Ackerman Shrier A, Chang A, Diakun-thibalt N, Forni L, Landa F, Mayo J, van Riezen R, Hardjono, T.
Organization:  Project PharmOrchard of MIT’s Experimental Learning “MIT FinTech: Future Commerce.”
2. Blockchain: Securing a New Health Interoperability Experience: Blockchain technologies solutions can support many existing health care business processes, improve data integrity and enable at-scale interoperability for information exchange, patient tracking, identity assurance, and validation. This paper suggests these processes can be supported by three most important applications: Creating secured and trusted care records, linking identities and recording patient consent decisions and patient directives within the secured patient record.
Authors:  Brodersen C, Kalis B, Mitchell E, Pupo E, Triscott A.
Organization:  Accenture LLP
3. Blockchain Technologies: A Whitepaper Discussing how Claims Process can be Improved: Smart contracts, Blockchain, and other technologies can be combined into a platform that enables drastic improvements to the claims process and improves the health care experience for all stakeholders. The healthcare industry suffers from an inability to clearly communicate costs in a timely and easy-to-understand format. This problem is a symptom of interoperability issues and complex agreements between providers, patients, health plans/payers and government regulators. These agreements are encoded in legal language with the intent of being defensible in court. However, the focus on legal enforceability, instead of understandability, creates problems resulting in hundreds of billions of dollars spent annually to administer an inefficient, outdated and complex process for adjudicating and paying health plan claims. 

 The process results in errors and often leaves the patient unclear on how much they need to pay. If these agreements were instead translated into computer code (smart contracts) leveraging Blockchain technologies, the claim process would not only be interoperable, but also drive standardization, research and innovation. Transparency and trust can be injected into the process when both the logic and the data driving these decisions is stored permanently and made available to all stakeholders through a peer-to- peer distributed database like blockchain. The result will be a paradigm shift toward interoperability and transparency, enhancing the speed and accuracy of cost reporting to patients. This paper discusses how smart contracts, blockchain and other technologies can be combined into a platform that enables drastic improvements to the healthcare experience for all stakeholders.
Author:  Culver K. 
4. Blockchain: A new model for Health Information Exchanges: Presentation of an implementation framework and business case for using Blockchain as part of health information exchange to satisfy national health care objectives.


 Authors:  Krawiec RJ, Barr D, Killmeyer K, Filipova M, Nesbit A, Israel A, Quarre F, Fedosva  K, Tsai L.
Organization:  Deloitte Consulting LLP

 5. A Case Study for Blockchain in Healthcare: “MedRec” Prototype for Electronic Health Records and Medical Research Data: A long-standing focus on compliance has traditionally constrained development of fundamental design changes for Electronic Health Records (EHRs). We now face a critical need for such innovation, as personalization and data science prompt patients to engage in the details of their healthcare and restore agency over their medical data. 

 In this paper, the authors propose MedRec: a novel, decentralized record management system to handle EHRs, using blockchain technology. The system gives patients a comprehensive, immutable log and easy access to their medical information across providers and treatment sites. Leveraging unique blockchain properties, MedRec manages authentication, confidentiality, accountability and data sharing—crucial considerations when handling sensitive information. A modular design integrates with providers’ existing, local data storage solutions, facilitating interoperability and making our system convenient and adaptable. 

 MedRec incentivize medical stakeholders (researchers, public health authorities, etc.) to participate in the network as blockchain “miners”. This provides them with access to aggregate, anonymized data as mining rewards, in return for sustaining and securing the network via Proof of Work. MedRec thus enables the emergence of data economics, supplying big data to empower researchers while engaging patients and providers in the choice to release metadata. 

 The purpose of this paper is to expose, in preparation for field tests, a working prototype through which we analyze and discuss our approach and the potential for blockchain in health IT and research.
Authors:  Ekblaw A, Azaria A, Halamka J, Lippman A. 
Organizations:  MIT Media Lab, Beth Israel Deaconess Medical Center
6. The Use of a Blockchain to Foster the Development of Patient-Reported Outcome Measures (PROMs): This paper suggests the use of Cognitive Behaviour Therapy as a modality to treat Mental Health disorders. This the author suggests is achieved by the use of various applications that allow the patient to record information using SMS or applications. These applications keep track of any emergencies, provides patient coaching and guidance, recording of daily progress and medication adherence. While many patients feel ashamed of their mental state and feel a stigma associated with conditions such as depression and anxiety, the anonymous nature of these applications may make it more likely for them to seek help. 

 These types of use cases are the first step in implementing blockchain technology as they help identify the system requirements and looks at the interactions between users and systems. In this case, the focus would be on personal health information that is highly sensitive and coming from mobile applications that require direct interaction between the patient and providers, as well as those involved in the care of the patient. 

 Each scenario that involves a transaction, or data being transferred from the application to those who have “signed” the transaction would be documented so the information flow and usage is understood. In this manner, the appropriate permissions would be granted and provenance could readily be established. Use of the Internet of Things in combination with Blockchain technology for Patient Reported Outcome Measures (PROMs).
Author:  Goldwater JC.
Organization:  National Quality Forum

 7. Powering the Physician Patient Relationship with ‘HIE of One’ Blockchain Health IT: ‘HIE of One’ links patient protected health information (PHI) to Blockchain identities and Blockchain identities to verified credential provider institutions to lower transaction costs and improves security for all participants. 

 HIE of One, (Health Information Exchange of One) shifts the trusted intermediary role away from the hospital and into the blockchain. The blockchain can also provide the link between physician credentials and patient identity.
Author:  Gropper A.

 8. Blockchain: The Chain of Trust and its Potential to Transform Healthcare – Our Point of View: This paper talks about Potential uses of Blockchain technology in health care including a detailed look at health care pre-authorization payment infrastructure, counterfeit drug prevention and detection and clinical trial results use cases. The paper also highlights what Blockchain is not. Some of the additional usecases as presented in the paper are listed below:


 Organization:  IBM Global Business Service Public Sector

 9. Moving Toward a Blockchain-based Method for the Secure Storage of Patient Records: Use of Blockchain as a novel approach to secure health data storage, implementation obstacles, and a plan for transitioning incrementally from current technology to a Blockchain solution. The author suggests a practical first step towards moving towards a blockchain enabled world, here is a suggested workflow by the author, from the submission: 

Author:  Ivan D.

 10. ModelChain: Decentralized Privacy-Preserving Health Care Predictive Modeling Framework on Private Blockchain Networks:   ModelChain, to adapt Blockchain technology for privacy-preserving machine learning. Each participating site contributes to model parameter estimation without revealing any patient health information (i.e., only model data, no observation-level data, are exchanged across institutions). 

 We integrate privacy- preserving online machine learning with a private Blockchain network, apply transaction metadata to disseminate partial models, and design a new proof-of-information algorithm to determine the order of the online learning process. 

 We also discuss the benefits and potential issues of applying Blockchain technology to solve the privacy-preserving healthcare predictive modeling task and to increase interoperability between institutions, to support the Nationwide Interoperability Roadmap and national healthcare delivery priorities such as Patient-Centered Outcomes Research (PCOR).
Authors:  Kuo T, Hsu C, Ohno-Machado L.
Organizations:  Health System Department of Biomedical Informatics, University of California San Diego, La Jolla, CA Division of Health Services Research & Development, VA San Diego Healthcare System.
11. Blockchain for Health Data and Its Potential Use in Health IT and Health Care Related Research: A look at Blockchain based access-control manager to health records that advances the industry interoperability challenges expressed in ONC’s Shared Nationwide Interoperability Roadmap.
In this usecase the authors discuss the use of blockchain technology with a data lake for scalability. All medical data would be stored off blockchain in a data repository called a data lake. Data lakes are highly scalable and can store a wide variety of data, from images to documents to key- value stores. 

 When a health care provider creates a medical record (prescription, lab test, pathology result, MRI) a digital signature would be created to verify authenticity of the document or image. The health data would be encrypted and sent to the data lake for storage. Every time information is saved to the data lake a pointer to the health record is registered in the blockchain along with the user’s unique identifier. The patient is notified that health data was added to his blockchain. In the same fashion a patient would be able to add health data with digital signatures and encryption from mobile applications and wearable sensors.


Authors:  Linn L, Koo M.

 12. A Blockchain-Based Approach to Health Information Exchange Networks: 
Sharing healthcare data between institutions is challenging. Heterogeneous data structures may preclude compatibility, while disparate use of healthcare terminology limits data comprehension. 

 Even if structure and semantics could be agreed upon, both security and data consistency concerns abound. Centralized data stores and authority providers are attractive targets for cyber attack, and establishing a consistent view of the patient record across a data sharing network is problematic. 

 In this work we present a Blockchain-based approach to sharing patient data. This approach trades a single centralized source of trust in favor of network consensus, and predicates consensus on proof of structural and semantic interoperability.

 The authors describe the Healthcare Blockchain as: 

Because a blockchain is a general-purpose data structure, it is possible to apply it to domains other than digital currency. Healthcare, we believe, is one such domain. The challenges of a patient record are not unlike those of a distributed ledger. For example, a patient may receive care at multiple institutions. From the patient’s point of view, their record is a single series of sequential care events, regardless of where these events were performed. This notion of shared state across entities, inherent to the blockchain model, is congruent with patient expectations. Also, it is reasonable to assume that each patient care event was influenced by one or more events before it. For example, a prescription may be issued only after a positive lab test was received. The notion of historical care influencing present decisions fits well into the blockchain model, where the identity of a present event is dependent on all past events.

Much like the Bitcoin approach, our block is a Merkle Tree-based structure[21]. The leaf nodes of this tree represent patient record transactions, and describe the addition of a resource to the official patient record. Transactions, however, do not include the actual record document. Instead, they reference FHIR Resources via Uniform Resource Locators (URLs). This allows institutions to retain operational control of their data, but more importantly, keeps sensitive patient data out of the blockchain. FHIR was chosen as a exchange format not only because it is an emerging standard, but also because it contains inherent support for provenance and audit trails, making it a suitable symbiotic foundation for blockchain ledger entries. FHIR in conjunction with the blockchain can serve to preserve the integrity and associated context of data transactions.


 A Blockchain-based approach to sharing patient data that trades a single centralized source of trust in favor of network consensus, and predicates consensus on proof of structural and semantic interoperability.
Authors:  Peterson K, Deedvanu R, Kanjamala P, Boles K.
Organization:  Mayo Clinic
13. Adoption of Blockchain to enable the Scalability and Adoption of Accountable Care:  A new digital health care delivery model that uses Blockchain as a foundation to enable peer-to-peer authorization and authentication.

The recent trends in Accountable Care based payment models have necessitated the adoption of new process for care delivery that requires the co-ordination of a “network” of care providers who can engage in shared risk contracts. In addition, the need for sharing in the savings generated equitably is key to encourage the network providers to invest in improved care paradigms. 

Current approaches to digitize healthcare focus on improvement of operational efficiency, like electronic records as well as care collaboration software. However, these approaches are still based on the classical centralized authorization model, that results in significant expense in implementation. These approaches are fundamentally limited in their ability to fully capitalize on the peer-to-peer digital work- flow revolution that is sweeping other segments of industry like media, e-retail etc. 

In this paper the author formulates a new digital health care delivery model that uses block chain as the foundation to enable peer-to-peer authorization and authentication. The author will also discuss how this foundation would transform the scalability of the care delivery network as well as enable payment process via smart contracts, resulting in significant reduction in operational cost and improvement in care delivery. 

In addition, this block-chain based framework can be applied to enable a new class of accountable tele-monitoring and tele-medication devices that would dramatically improve patient care adherence and wellness. Finally, the adoption of block chain based digital-health would enable the creation of varifiable “personalized longitudinal care” record that can form the basis of personalized medicine.

Author:  Prakash R.
14. A Blockchain Profile for Medicaid Applicants and Recipients: A solution to the problem churning in the Medicaid program that illustrates how health IT and health research could leverage Blockchain-based innovations and emerging artificial intelligence systems to develop new models of health care delivery. The solution envisions a Smart Health Profile by thinking of the blockchain profile simply as a broker that can answer questions about you as the need arises, your identity remains distributed. No one can ever see everything about you at once, including yourself. 

What makes the profile smart is that the services it provides can be quite intelligent. It can make sophisticated queries and actually trigger an action when certain conditions are met. For example, suppose you had a smart drug dispenser that recorded every dose you take as a transaction on the blockchain. A profile service might check everyday to see if you’ve taken your pill and automatically order a refill when you’ve used up all the pills. Over time, however, an AI service might become much more sophisticated to use a combination of information about your vital statistics from your wearable device and population studies of people using the various medications for your condition and either recommend a different regimen to your physician or simply cut out the middleman and direct your pharmacist to deliver you a new prescription.

The solution goes on to discuss the use of Blockchain in a medicaid scenario and a much more comprehensive solution as a distributed infrastructure for health.
Authors:  Vian K, Voto A, Haynes-Sanstead K.
Organization:  Blockchain Futures Lab – Institute for the Future
15. Blockchain & Alternate Payment Models:  Blockchain technology has the potential to assist organizations using alternative payment models in developing IT platforms that would help link quality and value.
Author:  Yip K.
References
The content provided in the examples above have been collated from the various submissions to the ONC’s Blockchain Ideation Challenge. You can write to me or connect with me, in case you are interested in receiving the copy of the documents.

 In my previous article on Blockchain I shared whats Blockchain and types of Blockchain. I also discussed some of the usecases companies and startups have focussed on developing Blockchain based solutions. In this article I will share some of the usecases based on Blockchain technology, in healthcare. 

 Alternatively, you could follow the links here

You can also review the various articles on Blockchain on the HCITExpert Blog.

[1]: Blockchain Articles by David Houlding:
https://www.linkedin.com/in/davidhoulding/detail/recent-activity/posts/

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Cybersecurity Trends in 2017

March 8, 2020 / CYBERSECURITY / 7 minutes of reading
Cybersecurity is in the news almost daily and Investment in cybersecurity, by established corporations or venture capital is rising. The stature and business significance of cybersecurity operations within organisations continues its rise to a strategic management issue in every organisation. A dearth of skills shortage continues to impede the progress of a successful cyber defense strategy that can be put in place, this is driving most organizations to increasingly look for outside help be entering into consulting and managed security services contracts.

Rapid Increase in the Investment in Cybersecurity

  • According to Gartner, worldwide spending on cybersecurity increased by 7% as compared to last year and will reach $86.4 billion in 2017.
  • Spending on both cybersecurity services and products is expected to keep growing into 2018, reaching $93 billion by the end of the year.
  • An Enterprise Strategy Group (ESG) survey found that for 39% of organizations, improving cybersecurity is the most important business initiative driving IT spending in 2017 and that 69% of organizations are increasing their cybersecurity budgets in this year alone. 
  • 81% of cybersecurity professionals agree that improving security analytics and operations is a high priority at their organizations.
  • Cybersecurity startup funding hit an all-time quarterly high in terms of number of deals in the first quarter of 2017, up 26% from the previous quarterly high. The trend held through the second quarter, which saw just one fewer deal (145 total) compared to the previous quarter. 
  • The amount of disclosed equity funding to cybersecurity companies has also recently broken records, reaching an all-time quarterly high of $1.6 billion in the second quarter of 2017, according to CB Insights.

From cybersecurity operations into strategic Digital Risk Management

Organizations today generally think of cyber-risk as internal network penetration and defense. But there is now a shift towards developing a more comprehensive risk management strategy that includes all the digital assests such as – websites, social networks, partner exposure, branding and reputation management and compliance. 
Says ESG: “Comprehensive Risk Management Strategy is a more holistic digital risk strategy designed to analyze threat intelligence, monitor deep web activities, track the posting of sensitive data, and overseeing third parties and partners.”
With the transformation of cybersecurity into comprehensive risk management, Gartner predicts that by 2020, 100% of large enterprises will be asked to report to their board of directors on cybersecurity and technology risk at least annually, which is an increase from today’s 40%. 
The key in presenting to the board, says Gartner, is to connect the cybersecurity program goals to business risks. An example would be a discussion of implementing a process for managing third-party risk to support a business’s cloud strategy.
Cybersecurity skills shortage, a problem needing attention
There are currently more than 348,000 open security positions, according to CyberSeek. By 2022, there will be 1.8 million unfilled positions, according to the Center for Cyber Safety and Education. And The industry needs and will continue to need new kinds of skills as cybersecurity evolves in areas such as data classes and data governance, says Gartner. 
According to the ESG Survey, Things aren’t improving at all, some survey results:
In 2016, 46% of organizations reported a problematic shortage of cybersecurity skills. In 2017, the research is statistically the same as last year; 45% of organizations say they have a problematic shortage of cybersecurity skills.
According to 2016 research conducted by ESG and the Information Systems Security Association (ISSA), 33% of respondents said that their biggest shortage of cybersecurity skills was in security analysis and investigations. Security analysis and investigations represented the highest shortage of all security skill sets.
Recent ESG research reveals that 54% of survey respondents believe that their cybersecurity analytics and operations skill levels are inappropriate, while 57% of survey respondents believe that their cybersecurity analytics and operations staff size is inappropriate.
The ramifications of skills and staff deficiencies are also apparent in the research. Cybersecurity operations staffs are particularly weak at things like threat hunting, assessing and prioritizing security alerts, computer forensics, and tracking the lifecycle of security incidents.
CISOs propose an easy fix: companies must work towards hiring more cybersecurity staff to bridge the knowledge and staffing gaps. In fact, 81% of the cybersecurity professionals surveyed say that their organization plan to add cybersecurity headcount this year.
However, its not that simple to do. According to the ESG research, 18% of organizations find it extremely difficult to recruit and hire additional staff for cybersecurity analytics and operations jobs while another 63% find it somewhat difficult to recruit and hire additional staff for cybersecurity analytics and operations.
Gartner recommends focusing the cybersecurity team on the most important tasks and automating the manual ones, such as log reviews. It tells CISOs to review their job listings to see if they are hiring for positions that can be outsourced.
Managed Security Services, SaaS and ITO route to managing security
All organizations need cybersecurity help, says ESG. When companies buy security tools, the product contracts include a professional services component that allow the companies to manage and ensure optimal usage of their security portfolio. CISOs can leverage the MSSPs and SaaS providers to outsource the relevant areas of their security portfolio.
According to Gartner, 40% of all managed security service (MSS) contracts in 2020 will be bundled with other security services and broader IT outsourcing (ITO) projects, up from 20% today. 
To deal with the complexity of designing, building and operating a mature security program in a short space of time, says Gartner, many large organizations are looking to security consulting and ITO providers that offer customizable delivery components that are sold with the MSS. 
As ITO providers and security consulting firms improve the maturity of the MSS they offer, customers will have a much broader range of bundling and service packaging options through which to consume MSS offerings. The large contract sizes associated with ITO and security outsourcing deals will drive significant growth for the MSS market through 2020.
IDC estimates that services will be the largest area of security-related spending over the next five years, led by three of the five largest technology categories: managed security services, integration services, and consulting services. 
Together, companies will spend nearly $31.2 billion, more than 38% of the worldwide total, on these three categories in 2017.
Increased confidence in cloud cybersecurity
Just about 5 years ago, concerns about adequate security were cited as one of the top reasons for not moving IT operations and assets to the cloud. This thinking has recently changed, accompanied by rapid cloud adoption by many large corporations. A recent survey by analyst firm ESG has found “improved security” reported as a benefit that has been realized by 42% of organizations that already leverage cloud-based data protection services.
Gartner explains the potential key benefit of cybersecurity in the cloud: Today’s data centers support workloads that typically run in several different places—physical machines, virtual machines, containers, and private and public cloud. Cloud workload protection platforms provide a single management console and a single way to express security policy, regardless of where the workload runs.
While there are known benefits of moving the security services to the cloud, Gartner warns that as the cloud environment reaches maturity, it’s becoming an increasing security target. As with most services, possibility of the cloud based security services being targeted and the rendering the service unstable and insecure. Organisations therefore should work on developing security guidelines as to how they use private and public cloud and prepare a cloud risks model.
AI and machine learning (ML) driven Cloud Security
ML algorithms have the ability and potential to help with employee productivity & security analytics, but the technology is in its infancy and not well understood, says ESG.  A survey of 412 cybersecurity professionals asked them to assess and characterize their knowledge of machine learning/artificial intelligence as it relates to cybersecurity analytics and operations technologies. Of the total survey population, only 30% of respondents claim to be very knowledgeable in this area. In other words, 70% of cybersecurity professionals really don’t understand where machine learning and AI fit their security portfolio.
Additionally, cybersecurity pros were asked about the status of deploying or are planning to deploy machine learning/AI technologies for cybersecurity analytics and operations in their respective organisations.
Only 12% say that their organization has done so extensively and 6% of respondents have no plans to deploy machine learning/AI technologies for cybersecurity analytics and operations. In the long run, most of the cybersecurity professionals did see the potential of AI and machine learning to help with automating manual tasks and ensure the management of skill shortage in the area.

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Its is important that organisations take the effort to gain knowledge about AI and ML and how it will impact Cybersecurity Services and Products. This way they will be able to be more proactive to understanding the adversarial capabilities of hackers. Many companies employ ethical hackers to find out the loop holes in their security portfolios and protocols.

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The Return of the Wearables, in a New Avatar by @msharmas

March 8, 2020 / #WEARABLES / 7 minutes of reading

IDC: Smartwatches accelerate in the second quarter, Device shipments grew 10.3% year over year to hit 26.3 million units during the second quarter of 2017; smartwatches grew 60.9%.

We are seeing the transformation of the wearables market with the total shipment volumes expected to maintain their forward momentum. According to the International Data Corporation’s (IDC) Worldwide Quarterly Wearable Device Tracker, vendors will ship a total of 125.5 million wearable devices this year, marking a 20.4% increase from the 104.3 million units shipped in 2016. From there, the wearables market will nearly double before reaching a total of 240.1 million units shipped in 2021, resulting in a five-year CAGR of 18.2%. [1]


The wearables market is entering a new phase


In the first phase of the market development, it was about getting the product out, to generate awareness and interest and getting the customers accustomed to the idea. This opportunity remains to be explored by the traditional and fashion brands as the scale of consumer electronics market evolves. Now, the wearables market is entering a new phase, opines IDC’s Ramon T. Llamas.

Now it’s about getting the experience right – from the way the hardware looks and feels to how software collects, analyzes, and presents insightful data. What this means for users is that in the years ahead, they will be treated to second- and third-generation devices that will make the today’s devices seem quaint. Expect digital assistants, cellular connectivity, and connections to larger systems, both at home and at work. At the same time, expect to see a proliferation in the diversity of devices brought to market, and a decline in prices that will make these more affordable to a larger crowd.” [1] 


 The phase 2 of the wearables development appears to be about taking the user data and provide analytics around the data to provide insights to the user, like step counts translate into a healthier heart. In this phase its about getting the customer to see the devices that actually augment the abilities to make lives easier, healthier and more productive, rather than another screen for the user. [3]

    Top Wearable Products [1]


     Watches: account for the majority of all wearable devices shipped during the forecast period. The report however shows that the basic watches (devices that do not run third party applications, including hybrid watches, fitness/GPS watches, and most kid watches) will continue out-ship smart watches (devices capable of running third party applications, like Apple Watch, Samsung Gear, and all Android Wear devices), as numerous traditional watch makers shift more resources to building hybrid watches, creating a greater TAM each year. The report suggests that the Smart watches, however, will see a boost in volumes in 2019 as cellular connectivity on the watches becomes more prevalent on the market.

     Wrist Bands: The report indicates a slow down in the market for the wristbands from 2016 onwards, but the market will be propped up with low-cost devices with good enough features for the mass market. However, the trend seems to focus on the users transitioning to watches for additional utility and multi-purpose use.

     Earwear: (this excludes the bluetooth headsets) are not counting. Instead, the report focusses on those devices that bring additional functionality, and sends information back and forth to a smartphone application. Examples include Bragi’s Dash and Samsung Gear Icon X. The report, also suggests the increase in the uptake of smarter earwear that centers on collecting fitness data about the user, real-time audio filtering or language translation.

     Clothing:  The smart clothing market took a strong step forward driven by the chines vendors providing connected apparel. The growth in this segment is seen to be driven by the adoption of the connected clothing by the professional athletes and organizations have warmed to their usage to improve player performance. For instance, the upcoming release of Google and Levi’s Project Jacquared-enabled jacket.

     Others: include lesser known products like clip-on devices, non-AR/VR eyewear, and others into this category. It will include vendors catering to niche audiences with creative new devices and uses.

    Top Wearable Devices by Product, Volume, Market Share, and CAGR [1]
    Product Shipment Volume 2017 Market Share 2017 Shipment Volume 2021* Market Share 2021* CAGR (2017-2021)*
    Watches 71.4 56.9% 161.0 67.0% 26.5%
    Wristbands 47.6 37.9% 52.2 21.7% 1.2%
    Clothing 3.3 2.6% 21.6 9.0% 76.1%
    Earwear 1.6 1.3% 4.0 1.7% 39.7%
    Others 1.6 1.3% 1.4 0.6% -16.0%
    Total 125.5 100.0% 240.1 100.0% 18.2%
    Source: IDC Worldwide Quarterly Wearables Device Tracker, June 21, 2017

    Global wearables market to grow 17% in 2017, 310M devices sold, $30.5BN revenue: Gartner | TechCrunch http://ow.ly/YFVu30eWQHL

    Like any technology market, the wearables market is changing [2]
    “Like any technology market, the wearables market is changing,” noted Ramon Llamas, research manager for IDC’s Wearables team. “Basic wearables started out as single-purpose devices tracking footsteps and are morphing into multi-purpose wearable devices, fusing together multiple health and fitness capabilities and smartphone notifications. It’s enough to blur the lines against most smart wearables, to the point where first generation smartwatches are no better than most fitness trackers, he says.

     Beyond the top 5 vendors of the wearables market, new entrants like fashion icons Fossil along with their sub-brands and emerging companies like BBK and Li-Ning, are tapping into niche segments of the wearables market. Fossil, is coming up with a luxury/fashion device, BBK focuses on child-monitoring devices and Li-Ning on step-counting shoes.

     “With the entrance of multiple new vendors with strengths in different industries, the wearables market is expected to maintain a positive outlook, though much of this growth is coming from vendor push rather than consumer demand,” said Jitesh Ubrani senior research analyst for IDC Mobile Device Trackers. “As the technology disappears into the background, hybrid watches and other fashion accessories with fitness tracking are starting to gain traction. This presents an opportunity to sell multiple wearables to a single consumer under the guise of ‘fashion.’ But more importantly, it helps build an ecosystem and helps vendors provide consumers with actionable insights thanks to the large amounts of data collected behind the scenes.”

    Top Five Wearable Device Vendors, Shipments, Market Share and Year-Over-Year Growth, 4Q 2016 (Units in Millions) [2]
    Vendor 4Q16 Unit Shipments 4Q16 Market Share 4Q15 Unit Shipments 4Q15 Market Share Year-Over-Year Growth
    1. Fitbit* 6.5 19.2% 8.4 29.0% -22.7%
    2. Xiaomi 5.2 15.2% 2.6 9.1% 96.2%
    3. Apple 4.6 13.6% 4.1 14.1% 13.0%
    4. Garmin 2.1 6.2% 2.2 7.6% -4.0%
    5. Samsung 1.9 5.6% 1.4 4.7% 37.9%
    Others 13.6 40.1% 10.3 35.5% 32.1%
    Total 33.9 100.0% 29.0 100.0% 16.9%
    Source: IDC Worldwide Quarterly Wearable Device Tracker, March 2, 2017

    Implications of Wearables in Healthcare


    Llamas, IDC. “Health and fitness remains a major focus, but once these devices become connected to a cellular network, expect unique applications and communications capabilities to become available. This will also solve another key issue: freeing the device from the smartphone, creating a standalone experience.”

    Its important to note here the scalability of wearables in a clinical setting requires Intention, Education and collaboration[7]. Some of the usecases highlighted for wearables in healthcare: 

    1. Managing Chronic Conditions of patients who might develop a secondary or tertiary complication because of a pre-existing condition (diabetic undergoing hip replacement surgery)

    2. Tracking vital signs
    3. Manage patients recovery at home (defensive medicine) instead of the recovery in a general ward, with help of remote monitoring
    4. Detecting Alzheimer’s, most common form of dementia
    5. Monitoring patients with chronic diseases and after hospitalization or the start of new medications for a decline in daily activity may help detect medical complications before rehospitalization becomes necessary
    6. Clinical Trials: Monitoring of recruits
    7. Smart Stethoscope for patients with cardiovascular disease
    8. Ear device to track body temperature fluctuations
    9. Temporary tattoo that senses vital signs
    10. Smart Glasses with AR enabled patient records and physician information system



    Finally, here is an interesting Infographic on Wearable Technology. 

    References

    1. Worldwide Wearables Market to Nearly Double by 2021, According to IDC: http://www.idc.com/getdoc.jsp?containerId=prUS42818517
    2. Wearables Aren’t Dead, They’re Just Shifting Focus as the Market Grows 16.9% in the Fourth Quarter, According to IDC 

    3. Xiaomi and Apple Tie for the Top Position as the Wearables Market Swells 17.9% During the First Quarter, According to IDC: 

    4. EXCLUSIVE: Fitbit Working On Atrial Fibrillation Detection | Time.com http://time.com/4907284/fitbit-detect-atrial-fibrillation/
    5. The 8 Best Fitness Trackers You Can Buy Right Now: http://time.com/4553111/best-fitness-trackers-fitbit-jawbone-2016/
    6. Can Your Fitness Tracker (Fitbit®) Save Your Life in the ER?: http://www.prnewswire.com/news-releases/can-your-fitness-tracker-fitbit-save-your-life-in-the-er-300246408.html
    7. Advocating for clinical wearables, the new normal in healthcare http://medcitynews.com/2017/08/advocating-clinical-wearables-new-normal-healthcare/?rf=1
    8. Global wearables market to grow 17% in 2017, 310M devices sold, $30.5BN revenue: Gartner: https://techcrunch.com/2017/08/24/global-wearables-market-to-grow-17-in-2017-310m-devices-sold-30-5bn-revenue-gartner/?ncid=rss
    9. What smartwatches and other wearables can’t track today— but might in the future – https://www.cnbc.com/2017/11/05/wearables-future-track-glucose-blood-pressure-mental-health.html

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    #IoHT is already delivering tangible cost savings, but continuous investment is essential – Accenture

    July 27, 2017 / IoT IN HEALTHCARE, OTHERS / 4 minutes of reading
    Image Source: https://www.accenture.com/us-en/insight-accenture-2017-internet-health-things-survey

    The Internet of Health Things (IoHT) is already delivering tangible cost savings, but continuous investment is essential

    In a recently published report by Accenture [2], based on a survey of 77 Healthcare payers and 77 Healthcare providers in the US, the reports findings indicate that healthcare leaders are at risk of missing out on substantial cost savings, if they don’t take the full advantage of Internet of Health Things (IoHT).


    The report indicated that by introducing more connectivity, remote monitoring, and information gathering IoHT can encourage more informed decisions, better use of resources and empowering healthcare users.

    According to estimates, the value of IoHT will top US$163 billion by 2020, with a Compound Annual Growth Rate (CAGR) of 38.1 percent between 2015 and 2020.[1] Within the next five years the healthcare sector is projected to be #1 in the top 10 industries for Internet of Things app development.[2]

    What is Internet of Health Things?

    Internet of Health Things (IoHT) is the integration of the physical and digital worlds through objects with network connectivity in the healthcare industry. IoHT transforms raw data in simple, actionable information and communicates with other objects, machines or people. IoHT can be leveraged to improve access to health, quality of care, consumer experience and operational efficiency 

    Source: Accenture Report
    Source: Accenture Report








    The report lists four major takeaways for the payors and providers: 

    The Time is Now

    Despite challenges with security and privacy, inaction is not an option. There are players outside of traditional healthcare organizations looking at these same industry challenges and considering ways to capture the opportunity. If providers and payers do not invest in demonstrating IoHT value now, they risk losing out to non-traditional players. Going forward, providers and payers must identify parts of the business where IoHT solutions may be applied to do things differently—and do different things to grow in the long-term.

    Measure and Build on Successes

    Providers and payers have already demonstrated value through IoHT—but they need to continue investments to better understand where programs are successful to prepare for future scaling. They need to measure effectiveness beyond the technology and then build on those areas of effectiveness quickly to offer value across the business. By demonstrating the benefits and best practices, providers and payers can strengthen business cases, encourage adoption and drive interoperability.

    Put consumers First

    Providers and payers must continue to incorporate IoHT solutions that drive better experiences and healthier patient outcomes, along with key medical and administrative cost savings initiatives. IoHT solutions offer the seamless collection of patient-generated health data, enabling providers and payers to provide more convenient, personalized and effective care. They must train their workforces to make IoHT a part of the “new normal.”

    Form Nimble Partnerships

    Technology and innovation partners can help payers and providers quickly test and learn how IoHT can drive business value to inform future scaling requirements. Strategy and change management partners can help to integrate these new technologies into their workflow, culture and training. 

    Key Findings of the Survey

    • 73% consider IoHT to be a major change, and consider IoHT to be a major disruptor in three years. 
    • however, 49% say the leadership at these organisations are yet to understand the potential of IoHT. 
    • As IT investments are going up so are the IoHT investments seeing to become a major budget line item.
    • Healthcare providers and payors are investing in IoHT in three areas of their businesses – RPM, wellness and operations. And these organisations are reporting real benefits from the initial programs.
    • While 57 percent of healthcare organizations surveyed say that their IT departments lead the IoHT charge, 26 percent say their research and development (R&D) divisions are leading their IoHT efforts and one in ten organizations even have dedicated IoHT subsidiaries or business units.
    • RPM Based IoHT: 33% of PROVIDERS report extensive operational cost savings from their RPM IoHT programs. 42% of PAYERS report extensive medical cost savings from their RPM IoHT programs. 
    • The majority of both providers’ (76%) and payers’(75%) RPM IoHT investments are focused on cardiac conditions. Interestingly, in the past, behavioral health has not received investment at similar levels to traditional high-cost areas such as cardiac, but the spotlight appears to now be shining on this area. Mental health, including behavioral health, is a relatively high priority for both providers (48 percent) and payers (55 percent)
    Source: Accenture Report, [2]


    References

    [1] “The Internet Of Medical Things–What Healthcare Marketers Need to Know Now,” January 2016, Victoria Petrock: Contributors: Annalise Clayton, Maria Minsker, Jennifer Pearson, eMarketer.

    [2] Accenture 2017 Internet of Health Things Survey 
    https://www.accenture.com/us-en/insight-accenture-2017-internet-health-things-survey


    And there you go, its fairly simple and we look forward to you sharing your experiences with our community of readers. We appreciate you considering sharing your knowledge via The HCITExpert Blog

    Team @HCITExperts
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    What is #ConnectedCare? Is the Healthcare Industry ready to embrace it in India?

    July 26, 2017 / IoT IN HEALTHCARE, OTHERS / 3 minutes of reading

    During the recently held #PhilipsChat the from Philips Healthcare set the agenda to discuss various aspects of what is Connected Care? 
    (http://blog.hcitexpert.com/p/connected-medical-devices.html) 

    Whenever a TweetChat is held, the moderator puts out an agenda for the discussion. Once its time, the participants share their point of view by Tweeting out their responses to the questions, tweeted by the moderator. 


     The Connected Care #PhilipsChat questions follow and I Look forward to You sharing your thoughts and point of view on the role of Connected Care in Healthcare: 

     1. How would you explain connected care in one line? 
    2. Is the healthcare industry ready to embrace connected care?
    3. How are your organization using connected care? Since when?
    4. Based on your experience, what are the elements to enable connected care further?
    5. How are you involving policy makers to embrace connected care?

     If we take these questions with an india context, how connected care can enable the affordability and accessibility to healthcare in India. These are the most often mentioned aspects of Healthcare, that needs to be addressed by not only the government, but also the Startup community willing to disrupt the Health Tech / Digital Health industry. 

     I have attempted to share my thoughts on Connected Care questions put forward during the tweetchat and I hope you will consider sharing your insights by filling in the form below

    1. How would you explain connected care in one tweet?

    An always connected channel of communication of care between the patient and provider, from “touch time” to “face time”  

    2. Is the healthcare industry ready to embrace connected care?

    In India, with the major push for digital services by the govt and private healthcare facilities, and with 350+MN internet users connected care is the only way to solve the accessibility to healthcare problem (1:3200 doctor to patient ratio)

    4. Based on your experience, what are the elements to enable connected care further?

    The connected care needs to bring about change in thought of how to use a connected care framework for the patient as well as the doctor. 

     For the patient, connected care is about 
    – experience that enables an ease of access to care
    – Ability to build their own healthcare record’s completeness 
    – Have a better set of processes and #workflows to manage their health and care 
    – Have the ability to find “patients like me” and be part of the community 

     For the Doctor, I believe it will be about 
    – how to glean new insights from the data stream
    – How to collaborate with a patient via an always connected model? What signifies the end of a consultation? 
    – To build constantly evolving care plans for their patients, based on realtime, near-realtime, time-delay, or frequency per day/week month updates
    – To evolve more treatment plans based on the insights that can be drawn from the raw patient data feed (an e.g.)
    – How to build a community and be part of a community of specialists to keep themselves up-to-date on the current research and practices.
    I am including the Questions as a Google Form, do consider sharing your insights into what is Connected Care? And how do you see it being enabled for the benefit of the patients and clinicians.

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