What is #BlockChain? Implications for Healthcare by @msharmas

In my previous article I discussed about the benefits and barriers to the use of an Integrated Health Information Platform. In healthcare the need for presenting the Information to the Right Person at the Right Time has been proven to improve outcomes in patient treatment.

Will HIE 2.0 benefit from the use of Blockchain in presenting the information to the Right Person at the Right Time? 


What is Blockchain?
Various definitions of Blockchain have been put across based on the context of the use. Some of these definitions are: 

A digital ledger in which transactions made in bitcoin or another cryptocurrency are recorded chronologically and publicly.

“The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.” Don & Alex Tapscott, authors Blockchain Revolution (2016)


The Blockchain is a decentralized ledger of all transactions across a peer-to-peer network. Using this technology, participants can confirm transactions without the need for a central certifying authority. Potential applications include, fund transfers, settling trades, voting etc.


Blockchain is a distributed system for recording and storing transaction records. More specifically, blockchain is a shared, immutable record of peer-to-peer transactions built from linked transaction blocks and stored in a digital ledger. [1]


A Blockchain is a data structure that can be timed-stamped and signed using a private key to prevent tampering. There are generally three types of Blockchain: public, private and consortium. [6]

How is Blockchain different?

Traditional databases are proprietary to the entity that maintains them and owns them. And the information stored within these databases are accessed only by providing access via an application or shared by the entity in some form of a distributed architecture. 

On the other hand, “blockchain is enabling a database to be directly shared across boundaries of trust, without requiring a central administrator. This is possible because blockchain transactions contain their own proof of validity and their own proof of authorization, instead of requiring some centralized application logic to enforce those constraints. Transactions can therefore be verified and processed independently by multiple “nodes”, with the blockchain acting as a consensus mechanism to ensure those nodes stay in sync.” [2]

A quite often stated example for explaining Blockchain is the Google Doc example. Earlier, collaborating on a document involved a serial approach to making changes to a document. Only once the author has completed the document, can it be forwarded to the next person to edit and provide feedback. 

But consider the Google Doc (or any of the other collaboration tools), once you have created a google doc, you can start creating the document and also share the same document with other collaborators who can also make changes to the document at the same time allowing for reconciliation of changes to be incorporated within the document to finalise it. The author takes the comments from the collaborators and generates the finalised document.

Blockchain: How it Works?

A transaction is requested. The transaction is broadcasted to the peer-to-peer network consisting of computer nodes. The network validates the transaction and the initiating entity’s status using relevant algorithms.  The transaction record is then considered to be verified.

Upon verification, the transaction record is added with other transactions to create a new block of data for the decentralized ledger of all transactions across a peer-to-peer network.

The new Block is added to the existing ledger of all transactions, i.e., the Blockchain. The transaction is now complete.

Types of Blockchains

Permissionless or Unpermissioned Blockchain allows anyone to join the network and participate in the block verification. For instance, a permissionless blockchain example is the Bitcoin.

Permissioned Blockchains restricts the nodes in the network who can contribute to the consensus of the system. Only permissioned nodes have the rights to validate the block transactions.

For instance, most enterprise Blockchains are permissioned blockchain and allow for privacy, scalability and fine-grained access control. [5]
Interoperability in Healthcare

There are various use cases that come to mind, when we talk about interoperability in Healthcare. (most are N:N interactions)

  1. HIMS to Lab Equipment
  2. HIMS to PACS
  3. HIMS to HIMS
  4. HIMS to Apps
  5. HIMS to Portals (Patient, Physician, etc)
  6. Portal to Portal
  7. Stakeholders to HIE
  8. Hospitals to Insurance

You can consider the number of stakeholders in the Interoperability ecosystem and continue to add them to the above list of use cases. And that allows one to understand the current fragmented nature of the Patient’s Healthcare Information. 

Each of the above stakeholders, generate the patient care record and have the need at one time or another to share this information with others in the ecosystem. We have already seen the benefits and barriers to information exchange. 

For the purpose of this blog, lets consider the Healthcare Information exchange use case. HIEs’ share the patient information in a network that is accessed by participating entities. The Patient information available on the HIE can be accessed as and when required by the patients’ treating doctor. 

The availability of a patient information, at the right place and at the right time was (one of) the intended purpose of a Health Information Exchange. HIE frameworks relied on a centralised or federated or hybrid architectures [3] to make the information available to the participants in the exchange. The exchange is maintained by an entity.

In the nationwide Interoperability roadmap defined by the ONC (US) [1]. They define the critical policy and technical components required as

  1. Ubiquitous, secure network infrastructure
  2. Verifiable identity and authentication of all participants
  3. Consistent representation of authorization to access electronic health information, and several other requirements


Additionally, the ONC challenge stated Potential uses to include:[6]

  1. Digitally sign information
  2. Computable enforcement of policies and contracts (smart contracts)
  3. Management of Internet of Things (IoT) devices
  4. Distributed encrypted storage
  5. Distributed trust

In India, 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. 

IHIP is envisaged to enable
  1. Better continuity of care, 
  2. secure and confidential health data/records management, 
  3. better diagnosis of diseases, 
  4. reduction in patient re-visits and even prevention of medical errors, 
  5. optimal information exchange to support better health outcomes

With the understanding of What is Blockchain, What is Interoperability in Healthcare and What are the use cases for Interoperability in healthcare, do you think Blockchain Technology can be used in Healthcare? Do share your thoughts and use cases.

In the next part of the blog, I will explore some of these use cases in healthcare and for the purpose of defining how Blockchain can help interoperability of Patient Transactions across healthcare facilities.


References

1. Blockchain Opportunities for Healthcare: https://www2.deloitte.com/us/en/pages/public-sector/articles/blockchain-opportunities-for-health-care.html


3. Health Information Exchange – Architecture Types https://corepointhealth.com/health-information-exchange-architecture-types

4. Bitcoin is the Sewer Rat of Currencies, interview of Andreas Antonopoulos by Mark Frauenfelder http://ow.ly/XDMe30bumBy

5. Blockchain – What is Permissioned vs Permissionless? by Deva Annamalai on Core Dump https://bornonjuly4.me/2017/01/10/blockchain-what-is-permissioned-vs-permissionless/

6. ONC Blockchain Challenge: https://www.healthit.gov/newsroom/blockchain-challenge
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Benefits of an Integrated Health Information Platform #IHIP by @msharmas

We have seen the benefits of Aadhar and how a public data repository can be used for public good. Population Health based clinical data repositories too can play a similar pivotal role in providing potentially great benefits


The use of Healthcare IT in the Indian context is picking up with most of the corporate hospitals going for the #EHRs and HIMS solutions. And these are present mostly in the Tier I cities and urban areas. There is a move now to get these solutions to the Tier 2 and Tier 3 centers as well. I would be looking to review reports that highlight percentage of IT enablement in Healthcare facilities, as part of follow up articles to this one.

The Center for Healthcare Informatics has rolled out an RFI detailing the requirements of an Integrated Healthcare Information Platform (IHIP). You can also visit the dedicated website to review the details of the IHIP RFI:
In this article I would like to highlight the benefits that will accrue from implementing such a solution in India. With no historic data of past implementations of such a system in India, I have reviewed the information available in journals and public domain regarding similar implementations across the world and what are the benefits and barriers in implementing an Healthcare Information Highway of patient healthcare data.


Benefits of Implementing an HIE

  1. Benefits of Implementing HIEs:
HIEs that have been implemented in the US have conclusively shown emergency departments gaining efficiency in patient visits with the use of HIE based solutions.
HIEs have shown to reduce the length of patient stay, readmission risk, and number of doctors involved in patient visits [1].
HLNY ER Dept Infographic_HIEGains.png
  1. Discharge Planning
One of the examples of benefits of an HIE, is the ability to generate alerts 24-hour to 48-hour prior to the patient’s’ discharge to Transportation services, Pharmacies at the patient’s location and alerts to help patient identify long term care and home care facilities. [2]
  1. Transfer of Radiology Images:
Currently the process of exchanging patient radiology images either does not exist or at best is time consuming with problems faced by the patients and providers treating the patients.
The ability to access and view radiology images is important for an accurate and timely patient diagnosis and treatment. Historically, the process of image exchange has happened via CDs with an understanding the receiving and reviewing physician will have the ability to view the PACS images leading to high costs and long time to diagnosis.
Enabling a Transfer to PACS capability helped in cutting these lacunae in the image sharing workflow, enabling providers to quickly share images with each other. [3]
  1. Vaccination and Immunisation details:
HIEs are now moving towards incorporating the exchange of patient immunisation details. Thereby enabling patient centered technology implementations.
  1. Disease Surveillance and Immunisation Records
IHIP will provide increased view of disease outbreaks and allow the governments at the state and national levels to deploy resources effectively and efficiently. IHIP based identification and surveillance of disasters and outbreaks is a big benefit of implementing a platform such as IHIP. And additional areas that provide a fillip to the IHIP-initiative needs to be identified and those aspects of the IHIP needs to be implemented in the initial stages.
  1. Medication Information Sharing via HIEs:
The ability for the patient to build and maintain an electronic Drug Profile is important for the continued care for the patient. Presence of a Comprehensive Patient Drug profile has direct correlation to improved patient safety. Improved medication information processing has a direct correlation to the benefits of an HIE like the IHIP since it will be able to provide a more complete clinical picture of the patient. [4]
  1. Telemedicine service enabled by HIEs:
Telemonitors will be able to provide patients a way to measure and record their vital signs daily from home using a touchscreen tablet/ mobile/ PC. The information will be then wirelessly transmitted to nurses monitoring the information for changes, giving patients with, complex disease states such as heart and respiratory conditions, a sense of empowerment around their health. Telehealth has far reaching benefits for specialists providing their services to patients in the rural, underserved and non-tier I cities. With the presence of digital payment gateways and transactions, Telemedicine is fast becoming a viable business model for certain types of visits(e.g., follow-ups, referrals). [5]
  1. New Use Cases for an HIE:
When HIEs have been implemented, new use cases can emerge that extend the usefulness of HIEs. For example, HIEs have been able to send hospitals alerts and reminders when patient transitions occur, device to device data transport, sending and receiving of claims attachments, and exchanges of documents for referrals [6]
  1. Security of Patient Information (PHI):
The greatest benefit of an IHIP-like solution is the Implementations of Security protocols for transport and transfer of patient information between healthcare facilities and between patients and hospitals. This ensures creation of “Trust” centers of patient data.
  1. Improves the Trust in sources of information
One of the reasons a physician would order for a repeat test for a patient in case of a referral, would be “Trust” on the presence of a similar/ same test result available for the patient in an earlier visit. Enabling information sharing via IHIP in a standardised and secure format will enable “Trust” between healthcare facilities as trusted sources of information. [7]
  1. Strategies to avoid Information Blocking:
Information Blocking has been known to be a major cause of hindrance to the benefits brought out by an HIE. Information Blocking is healthcare facilities not sharing patient healthcare record information causing holes in the episodes of care of a patient’s longitudinal record. To avoid this from happening, “Increasing transparency of EHR vendor business practices and product performance, stronger financial incentives for providers to share information, and making information blocking illegal were perceived as the most effective policy remedies,” wrote researchers. [8]
  1. Paradigm Shift in HIE from 1.0 to 2.0:
HIE 1.0 was characterized by a focus on “the noun,” that is trying to address perceived market failures by solving a wide variety of rich use cases through comprehensive interoperability.
By contrast, HIE 2.0 focuses on the verb that is trying to meet market needs most pressing to participating providers; HIE 2.0 has fewer legal challenges because it is trying to tackle less complex use cases and in many instances has the ability to marshal financial, technical and organizational resources. Tripathi also pointed out that HIE 2.0 comes in many shapes and sizes including point-to-patient; point-to-point; vendor-specific; transaction-specific national level; enterprise-level HIE organizations; State-level and regional collaborative HIE organizations and National level collaborative HIE organizations.
Three areas identified to spur innovation and move towards HIE2.0 were: Lab data transmission, Lightweight directed query of patient information, eCPOE and measures.

Problems Implementing HIE: A review of Global HIE Experiences

  1. Unspecified Interoperability Standards:
Barriers to HIE relate to incomplete and unspecific interoperability standards and the cost of interfacing the EHR with the HIE.  The lack of mature, agreed standards around interfaces, patient consent and patient identification are significant barriers to success.
  1. Accurate patient identification is not only a data management and data quality issue, it’s also a patient safety issue
  2. Clinical Information Generator and Vendor relations
In the India context, healthcare facilities like hospitals, laboratories, pharmacies deploy systems that are proprietary in nature and not necessarily standards based. In the event of strained relations between healthcare facilities and respective vendors, there is a need to consider addressing the need to have the patient related information to be relayed to the patient in a HIE readeable format. This information can then be uploaded by the patient thereby ensuring the continuity of care records are maintained in the IHIP, specific to the patient.
In this scenario, there could be a loss of updates to the public health based registries and the hospital based registries and it should be incumbant on the hospital to ensure the data is transmitted before the changeover of systems happens.
  1. Identifying ROI for various Stakeholders
A study needs to be enabled by the government at the national and state levels that will study the benefits of implementing interfaces that will share information between the Healthcare facilities and the IHIP. Potential savings can be quantified based on cost and projected savings in improved efficiencies enabled by the implementation IHIP towards patient safety and care coordination for the stakeholders.
Additionally, its important to quantify the cost of implementing HIE-based interfaces by the various healthcare entities (like Hospitals, Laboratories, Diagnostic centers, pharmacies, etc). It will be important to identify the Revenue Streams to sustain IHIP data sharing, and how can it be sustained by the stakeholders.
  1. Breach of Security of Data contained in IHIP or connected interfaces
We have seen various types of hacks that have breached the security of patient records stored in hospital systems. Enabling security at various levels needs to be ensured before any of the Stakeholders connect with the IHIP. Security guidelines will have to be defined and adhered to and reported on a regular basis as a regulatory requirement.
Security is also necessary at the IHIP level which has been defined as a main requirement for developing the IHIP infrastructure.
In the US Architecturally, RHIOs employ either the CHMIS approach of a centralized database, the CHIN model of federated independent databases, or some combination of the two, hybrid model.
  1. Usability & Access to Information Ok, so the data about a patient has been stored in the Data Repository for all to access and review at the time of emergencies, for enabling a continuity of care record for the patient and for generating population health management analysis. But, what if the data is not easily accessible, the functionality to access the care information of the patient, requires multiple access requests and clicks and permissions. What if, the data has now been stored in the public data repository, who can access it? Who can view it? Can there be an unauthorised data access by persons not connected to the health care of the patient? [25]
  2. Information Blocking:
For-profit EHR vendors have a natural vested interest in increasing revenue by limiting the flow of data.
“The specific forms of and perceived motivations for information blocking were harder to predict a priori,” Adler-Milstein & Pfeifer explain. “What we found in relation to specific forms is that EHR vendors appear to most often engage in information-blocking behaviors that directly maximize short-term revenue. Our respondents reported that EHR vendors deploy products with limited interoperability and charge providers high fees unrelated to the actual cost to deliver those capabilities or refuse to support information exchange with specific EHRs and HIEs.”
Hospitals and health systems likewise utilize information blocking as a means to prevent clients from seeking services elsewhere to keep from losing out to the competition.
“In our results, the most commonly reported forms of information blocking among hospitals and health systems point to their interest in strengthening their competitive position in the market by controlling patient flow, which has been reported in other studies,” they wrote.

Interoperability in Healthcare: Some thoughts to share

Having followed the implementations in India for sometime now, I always wonder why interoperability is not a top priority or not implemented in most systems. They are HL7 compliant, but are they really interoperable? And I dont mean the part from HIMS to Lab or Rad equipment, that part is fairly well defined and documented. 

– But from the Patient to Hospital to Patient
– Patient to Insurance to Patient
– Patient to app to hospital to Patient

Take for instance most systems are able to share the discharge summaries as emails to patients, and a print out, even today. But on discharge can the patient “share” her discharge summary from an app or application to another practitioner who takes care of the patient rehab? Are for instance, the systems involved in the above use case, interoperable? 

Another point, how many Healthcare Apps (the production versions) have any data sharing via standards? They can however email PDFs of the recorded data. So what can be done to enable out-of-the-box interoperability in the Healthcare Apps? With the growing number of mHealth Apps, we will soon find ourselves in another new set of “Data-Silos” being created on a daily basis.

Recently we moved from Cash to Cashless to Less Cash scenarios … so is it right to say, in healthcare context, we are working from a Paper to Paperless to Less Paper scenario in Healthcare before going totally paperless? 

And if so: 

1. What will be the business case for interoperability and for sharing the discharge summary/ medications in a format that is easily exchangeable?

2. Can a Healthcare IT think tank, work on defining the standards of “workflow” of the data being generated in healthcare today? Starting from the Patient through the healthcare ecosystem and back to the Patient?


3. Can the Healthcare IT vendors form a group of HIMS, LIMS, Pharma Apps, HomeCare solutions that enable a “Patient Data Workflow” exchange group (a mini-IHIP) that actually enables the “Interoperability” of patient data as a great showcase. It could perhaps be tied to the IHIP effort or NDHA. It adds onto the work that is being planned in the Phase 1 of the IHIP project, by being able to provide feedback on issues, solutions, recommendations, pain points etc.

Its important to note, that a system like IHIP has a potential to solve the accessibility of patient care problem in India. My view is that there is a need to see interoperability from a Patient’s point of view rather than from the point of view of “Systems”. There is a need to map the flow of data from the Patient and back to the Patient, and this can help in enabling a radically different approach to interoperability in Indian Healthcare.

With Aadhar based solutions allowing for the consumer information to be securely transmitted and verified, it only behoves well if we were to adopt an “HIE of Patient” approach to IHIP wherein the Information is exchanged between various stakeholders in the Patient’s Care Continuum and that information finally rests with the Patient’s Electronic Health Record (PEHR). With the EHR standards mandating the Healthcare Information belongs to the patient, it will be extending that mandate to IHIP.

References

  1. NY Health Information Exchange Improves ED Quality, Efficiency
  1. HIE Partnership to improve Health Data Exchange of Imaging
  1. Health information exchange and patient safety
  1. Vermont HIE adds telehealth component
  1. DirectTrust HIE growth shows priority of Interoperability
  1. Health information exchange: persistent challenges and new strategies
  1. Health Information Exchanges report Information Blocking
  1. Maine Rural Veterans Health Access HIT Strategies
  1. The Value Of Health Care Information Exchange And Interoperability (a must read paper on how the costing for HIEs can be done)
  1. Health information exchange: persistent challenges and new strategies
  1. Information Blocking: Is It Occurring and What Policy Strategies Can Address It?:
  1. What is HIE?:
  1. Health Information Exchange?:
  1. HIE Benefits?:
  1. Guide to Evaluating Health Information Exchange Projects
  1. HIMSS Library for Information on HIEs
  1. Health Information Exchange – Overview
  1. 10 things to know about health information exchanges
  1. Selecting & Using a Health Information Exchange | AMA
  1. The Sequoia Project eHealth Exchange
  1. What is Health Information Exchange? | HIMSS
  1. IHIP, India
  1. Are Data repositories set to become data dumps? https://www.digitalhealth.net/2017/04/another-view-neil-paul-21/
  2. Powering the Patient Relationship with Blockchains: https://www.healthit.gov/sites/default/files/7-29-poweringthephysician-patientrelationshipwithblockchainhealthit.pdf
  3. Lessons from the UK | Healthcare IT News


Author

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Manish Sharma

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Understanding the Medical Diagnosis processes, to build an AI based solution by @msharmas


Human Intelligence

is The ability to adapt one’s behavior to fit new circumstances.

In Psychology, human intelligence is not regarded as a single ability or cognitive process but rather as an “array” of separate components. Research in building AI systems has focused on the following components of intelligence: [1]

  • learning,
  • reasoning,
  • problem-solving,
  • perception, and
  • Language-understanding

These components of human intelligence are also utilized during diagnosing a patient and defining the treatment plan and protocol for the patient.

The process of Medical Diagnosis


The process of how a Doctor goes about her diagnoses of a patient, is the ability of a Doctor to adapt to varying presenting illnesses of her patients.

  • Identify the Chief complaint of a patient
  • Gather information about the history of present illness
  • List the possible diagnosis & record the differential diagnosis for a patient
  • And then perform relevant diagnostic tests to determine the most likely causes for the presenting complaints

The Doctor initiates the process of identifying the most likely cause of the patient’s presenting illness and then based on the results of the diagnostic tests, proceeds to confirm a diagnosis and then proceed towards defining a treatment plan for enabling the patient to recover from the disease.
 

In the above simple process defined for a medical diagnosis, the Doctor (based on her training) makes use of all the “components of intelligence” to arrive at the most likely treatment plan for a patient. The process obviously gets more involved and complex depending on the type and nature of diagnosis.

Medical Diagnosis or Medical Algorithms?


From the above “very simple example” it’s clear that the doctor uses her learning and reasoning to proceed towards the best possible treatment pathway for the patient. And this can be treated as a series of Questions that help the doctor arrive at the “confirmed diagnosis” for the patient.
 

The process of Medical Diagnosis can then be treated as an Algorithm that helps the doctor arrive at a conclusion based on the presented facts.
 

Dictionary defines an “Algorithm” as, a process or set of rules to be followed in calculations or other problem-solving operations
 

The doctor in the above scenario has being processing via a set of rules and calculations and problem-solving operations to arrive at the confirmed diagnosis.
 

The doctor goes through a perception analysis to determine what specifically is presented based on the patient’s illness and then determines based on, not only the diagnostic test results, but also based on other parameters of a patient’s active and confirmed diagnosis.
 

Medical Diagnosis work in clinical practice generally has four models: [4]

  • Pattern Recognition, wherein the doctor recognizes the current patient’s problem based on her past experiences with other patients, e.g., Down’s syndrome.
  • Hypothetico-deductive, wherein the doctor performs a certain battery of tests to test a hypothesis, a tentative diagnosis
  • the Algorithm Strategy: the algorithm strategy has been used in Healthcare and has been represented using Medical Logic Modules [5], Arden Syntax for Medical Logic Systems [6] and Clinical Pathways [7] and finally the
  • Complete History Strategy has been defined to be the identification of Diagnosis by possibility. Evidence based medicine is then used to come to a conclusion of the final diagnosis. [8]

The training process to arrive at a Medical Diagnosis has been used in the past to the development of expert systems or Clinical Decision Support Systems (CDSS). Early medical AI systems have tried to replicate the clinical training of a doctor into meaningful implementations of AI in healthcare.

Usecase for Artificial Intelligence in Healthcare


Understanding the process and workflow in healthcare is going to be important in implementing solutions that are “aware” and intelligent. And the systems that need to be developed for Healthcare need to be able to assist the clinicians with systems that are more close to the clinicians natural daily workflow.


Consider the current scenario of a physician meeting with a patient in a clinic setting, with the current systems in place the “Patient Visit” workflow generally involves the doctor having to divide her time between talking to the patient, examining the patient and recording the findings on an EHR (electronic health records) system. Most such visits can last from 5 minutes to an hour depending on the specialty (for instance, general medicine to mental health). Additional complexity is added to the workflow based on the patient diagnosis.
 

There have been many studies that have recorded the doctor’s reasons for resistance to enter the visit data into a system [9]. A time and motion study of a patient – doctor interaction can be revealing in an EHR vs a non-EHR setting. While EHRs have shown their ability to reduce potential errors (as has been well documented in the report, to err is human) the additional steps of transcribing the visit data into an EHR is generally seen by the doctors as being a disruption in their natural visit or encounter workflow.
 

On the other hand, take into consideration a study of the workflow of a pathology department such as biochemistry or hematology, where the technology implementation is relatively easily accomplished. The pathology departments main “Entity”(from a systems perspective) to be processed is the patient sample and the level of automation required to process the various tests that need to be performed on the sample is quite well defined by its degrees of freedom, the test ordered by the doctor. Similarly the entity in a radiology department is the image that is the outcome of a radiology exam.
 

In radiology department for instance, an AI-based solution can enable operations at scale for enabling reading of radiology images from rural areas, where in the images get uploaded by the medical assistant or radiographer at the remote location. The AI systems now have the ability to read and report the images with increasing accuracy, but we still have some way to go before we achieve a greater deal of accuracy.
 

On the other hand, the “Entity” in a patient doctor interaction in a visit, the patient, has many more touch points within the patient care continuum and the level of complexity of this interaction needs to be dealt with in a completely different approach. While the processing in a pathology or radiology department is based on the sample or an exam, which is a snapshot at particular point in time, the treatment of a patient constantly needs to be monitored and presents more data points on an ongoing basis.
 

An AI-based solution to help a physician therefore needs to be applying for instance, the four models of medical diagnosis to a patient visit before we can call a patient visit as an intelligent or aware encounter.
 

If a doctor divides her time between listening to the patient regarding her present illness, and simultaneously recording the information on a computer system, there has been a disruption in the doctor’s natural workflow of focusing on the patient, of listening to her present illness, asking questions about onset, etc. and reviewing the results of the investigations and radiology reports. The doctor is trained to handle all these data points and process the information from the perspective of the four aspects of the medical diagnosis training of the physicians.




Here is an interesting story you would like to review showcasing a doctors 35-hr shift in Delhi, India. By the way the story lends itself to creating some really interesting “Intelligent Digital Assistants” for the doctors.   It also presents to experts developing AI based solutions for Healthcare, a fantastic time and motion study of a Doctors’ shift and the touch points to where the technology can be integrated into the Doctors “workflow”
  
Current systems do not allow that, they tend to focus on implementing a strategy of recording by exception, by recording only the exceptions and all the other aspects being marked as normal, for instance. While such aspects have been proposed and devised by working with the physicians, still they are workarounds to do what the technology of today allows or allowed in the past. 

These are re-creations of paper based systems that have been translated to an electronic health recording system.
 

The Patient – Physician interaction needs to be revamped, in the current information technology systems by enabling the various components of human intelligence we have highlighted earlier:

  • learning,
  • reasoning,
  • problem-solving,
  • perception, and
  • Language-understanding

Ideal scenario for a Patient – Physician interaction would be the implementation of a solution that “records” all of the conversation during a visit and automatically creates the Visit note, by understanding the Chief complaint, presenting illness, history of the patient, procedures ordered, medications prescribed, follow-ups or referrals ordered, et al. Purely based on the conversations between the doctor and the patient.
 

Such a scenario requires the implementation and collaboration between various components of the Artificial Intelligent ecosystem. And that will be the true and useful implementation of AI for the Patient and Physician interaction, enabled by Artificial General Intelligence capabilities.
 

The change needs to be implemented by not only incorporating the changes to the core algorithms, but it also involves incorporating changes to the UI and UX design changes. AI based solutions will force a change in the way current systems have been designed.

Its important to explain the way the physician thinks while interacting with the patient. 

It’s been of late seen technology solutions to be hindering the doctor patient visit process. And hence it my endeavor to try to present the case that AI while hyped to be replacing doctors, is not yet ready for the prime time. There are areas of immense potential, radiology image processing for instance but then that’s from a process improvement perspective. And not doctor patient interaction perspective. 

For years now, technology in healthcare has been trying to take the paperless approach and has tried to “replace” paper while forgetting that there is a more important component of enabling workflow in the Patient Care Continuum. 

And it’s because of this reason, I argue that whilst it’s great for the technology hype cycle to see AI as the deliverer, we need to remind ourselves once again, that it’s not about going paperless, but ensuring the 15 min that a patient gets of the doctor’s time, are well spent with the conversation being patient focused and the technology receding to the background and generating the relevant care records.

In other areas of healthcare too it is about process improvement.

And add to that the fact that in most implementations in healthcare, clinical documentation is either cumbersome or non existent, the hype cycle of AI needs to consider these issues. From my understanding since the underlying data is fragmented, not standardized and not interoperable in majority of the instances; I took a shorter term view of the AI implementation in the systems in this article.

Current Status of Artificial Intelligence in Healthcare

There has been data explosion in Healthcare not only from the perspective of the patient care continuum, but also from the point of view of the resource management and scheduling, inventory and purchase management, insurance, financial management, etc.
 

While most of the current focus has been on building AI-based solutions that are in the patient care continuum, there are definitely many more areas within a healthcare organization that will benefit from the implementation of intelligent systems.
 

Just the other day, I attended a conference around AI and the panelists were mentioning the following uses of AI

  • ecommerce recommendations
  • learning for students based on concepts in school
  • autonomous cars
  • AI based treatments plans for cancer patients
  • intelligent assistants, chatbots
  • Teaching computers to see; etc.

And while they all highlighted areas of advancement in AI tech, they are yet to reach the ability to currently create a system that converts a doctor patient conversation to actionable events that can spawn workflows that needs to be instantiated based on the ever changing patient condition.

In the near-term, I see there will be specialized implementations of AI that will enable the brute power of technology to present the best case scenario for a particular patient condition, but an AI Physician is still a work in progress. This has been shown to be a success with the advent of cancer care solutions using IBM Watson. 

The AI systems are being implemented in various scenarios in healthcare and you could consider them to being “trained” and being presented with a great amount of data and studies. As more data is presented to these AI systems, their level of accuracy will only improve and provide benefits in-terms of scale and reach thereby reducing the time to diagnosis and time to treatment for patients having affordability and accessibility issues in healthcare.

Artificial Intelligence has already started making its way into healthcare, with 90+ AI startups getting funding to deliver solutions like;
  • helping the oncologist define the best treatment plan specific to each patient
  • a virtual nursing assistants, to follow-up with patients post discharge
  • drug discovery platforms, for new therapies
  • Medical Imaging and diagnostics
  • The use of AI in diagnosing diseases, patient education and reducing hospital costs
  • You can also find a great discussion on machine learning, wherein how machine learning could replace/ augment doctors via the health standards podcast with Fred Trotter.

Some of the other areas where AI is being implemented in Healthcare. Microsoft, Apple, IBM and other major players are all looking to AI help in curing people. And they are forming a group that creates the standard of ethics for the development of AI.

AI in healthcare also has a potential to be leveraged to be implemented in the following aspects of Healthcare Industry: 

  • Billing and Insurance Workflow, Insurance reconciliations and provider workflows can be enhanced by enabling total automation of the processes by enabling handling of the insurance claims by AI based Insurance agents. The exceptions and outliers can be escalated for manual interventions and closures.
  • Improving customer experience in healthcare by providing a 360 degree engagement, the SMAC based solutions will use the power of integrating the data streams from multiple sources to help deliver a better service to the patients.
  • Inventory and Supply chain processes can benefit from AI driven optimization by incorporating e-commerce driven innovations that allow for a democratization of product to vendor mix by searching and delivering the best cost options to the procurement department. Thereby bringing the costs down. Logistics improvements delivered in other industries need to come to healthcare to allow for the reduction in the cost of procurement of drugs, devices and durables. AI will help organizations in identifying variable costs and help them understand how to handle scenarios that will present themselves in an ongoing basis.
  • AI enabled resource management and scheduling will allow for identifying areas that need to be staffed with more resources and when additional resources need to be hired to meet with the increasing demands or provide elastic resource management based on ever changing operational demands. Booking appointments with doctors, will become a job taken up by Bots or AI assistants, enabling the nursing and administrative staff to focus more on delivering care and enhanced service experience for the patients.
  • AI-based people management systems will help hospitals in recruitment, retention and performance management of their employees. By presenting an analytics driven approach to people management, systems will be able to help employees to be trained to take up newer roles and responsibilities.

So by when will AI really take over Doctors?
 
It’s clear from the image above, that estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil, and Anders Sandberg and Nick Bostrom), “along with the fastest supercomputer from TOP500 mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years” [10]. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about where consciousness arises

Based on the above point of view, an interesting question to ask today:
If a Doctor goes through 7+ years of training to become a specialist, how many days will it take for an AI based Physician?

The answer perhaps lies in the following statements

Chief scientist and AI guru Andrew Ng of Chinese search giant Baidu Inc. once put it, “worrying about takeover by some kind of intelligent, autonomous, evil AI is about as rational as worrying about overpopulation on Mars.” [11], [12].

And,

What is it that makes us human? It’s not something that you can program. You can’t put it into a chip. It’s’ the strength of the human heart. The difference between us and machines.
– Terminator Salvation, 2009

References
[1]: AlanTuring.net What is AI?
[3]: Improving Diagnosis in Health Care | The National Academies Press https://www.nap.edu/catalog/21794/improving-diagnosis-in-health-care
[4]: The diagnostic process in general practice: has it a two-phase structure? http://fampra.oxfordjournals.org/content/18/3/243.full
[5]: Managing Medical Logic Modules.
[6]: HL7 Standards Product Brief – Arden Syntax v2.9 (Health Level Seven Arden Syntax for Medical Logic Systems, Version 2.9) http://www.hl7.org/implement/standards/product_brief.cfm?product_id=290
[7]: Clinical Pathways via Open Clinical, knowledge management for medical care http://www.openclinical.org/clinicalpathways.html
[8]: Sackett DL, Haynes RB, Guyatt GH, Tugwell P. Clinical Epidemiology. Boston: Little, Brown and Co., 1991; 3–18.
[9]: Barriers for Adopting Electronic Health Records (EHRs) by Physicians https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766548/
[10]: Artificial General Intelligence,
[11]: AI guru Ng: Fearing a rise of killer robots is like worrying about overpopulation on Mars
[12]: The Artificially Intelligent Doctor Will Hear You Now
[13]: Why we are still light years away from full artificial intelligence | https://techcrunch.com/2016/12/14/why-we-are-still-light-years-away-from-full-artificial-intelligence/
[14]: AI In Healthcare Heatmap: From Diagnostics To Drug Discovery Startups, The Category Heats Up

[15]: Doctor’s 35-hr shift on 8 bananas, a toilet in nearby cafe
http://indianexpress.com/article/india/india-others/doctors-35-hr-shift-on-8-bananas-a-toilet-in-nearby-cafe/ 
[16]: Gigerenzer’s simple rules by NS Ramnath on Founding Fuel 
http://www.foundingfuel.com/article/gigerenzers-simple-rules/
[17]: A.I. VERSUS M.D: What happens when diagnosis is automated? By Siddhartha Mukherjee
http://www.newyorker.com/magazine/2017/04/03/ai-versus-md

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The Current Status of 8 Future Technologies on Healthcare by @msharmas

It’s mid-2016, and here is a look at the current status of 8 Future Technologies that might be having a significant impact on Healthcare


Most if not all these technologies will make an impact on Healthcare, and hence it is important to understand the various scenarios and the stories detailing how the experts from across the world are incorporating these technologies in healthcare

1 Internet of Things

By 2020, there are expected to be 50B IoT devices with a total economic impact of $3.9Trillion – $11.0Trillion across all the industries, out of which $1.6 trillion impact in the “Human” segment.

Experts have identified the various areas in Healthcare, where IoT-based solutions can be implemented in healthcare. 

  • IoT refers to any physical object embedded with technology capable of exchanging data and is pegged to create a more efficient healthcare system in terms of time, energy and cost.
  • Dr. Vikram in his article on how IoT can transform healthcare opined the benefits of remote patient monitoring in emergency cases
  • Dr. Pankaj Gupta, noted in his article for IoT-based solutions to be aggregators of healthcare data from primary, secondary and supporting care market will begin to be aggregated. It will be in the interest of Insurance, Pharma and Govt to support IoT driven Healthcare Market Aggregation
Digital Health startups are working on the following categories as showcased in The Map of Healthcare IoT

  • Clinical efficiency, 
  • clinical grade biometric sensors/ wearables, 
  • consumer home monitoring, 
  • brain sensors/ neurotechnology, 
  • fitness wearables, 
  • sleep monitoring and infant monitoring

IoT platforms need to be created to ensure the utilization of data being generated by the IoT devices deployed in healthcare. Absence of platforms to aggregate IoT device data will result in loss of meaningful and contextual insights being drawn for the patients’ conditions.
 
Here is an Infographic, by Team HCITExperts, IoT in Healthcare, Types of Opportunities

2 Augmented Reality

Pokemon Go happened and augmented reality has triggered the imaginations of the innovators to work on bringing the technology to Healthcare

By 2020, an IDC report states AR – VR revenue will hit $162Billion by offering major applications for healthcare and product design.

In a recently concluded Intel developer conference, Microsoft’s Windows chief Terry Myerson announced a partnership with the chip maker that will make all future Windows 10 PCs able to support mixed reality applications.

For instance, Live 3D imaging is one of the hottest topics in optics today, transforming medical imaging capabilities and delivering the immersive experience behind augmented and virtual reality.  

Tim Cook in a recent interview indicated Augmented Reality to be a bigger market than virtual reality.

3 Virtual Reality

With VR technology projections reaching $3.8Billion by 2020, there will be an increase in the use of VR technologies in Healthcare

Virtual reality has an increasing number of implementation opportunities in Healthcare for education, training and patient treatment.

While the cost of using VR in healthcare is still something that needs to be dealt with, partnerships like the one with Intel and Microsoft only bodes well for bringing the technology mainstream and be cost effective.

VR tech is currently being used to 

  • virtually zoom around the patient’s brain to pinpoint an aneurism before the operation. 
  • 3D virtual renderings of the patient’s anatomy lets physicians get a very real experience before operating on the patient
  • the Virtual Reality is being used to present the patient a virtual human agent that replicates a Doctor & Patient communication, where patients can get their questions answered in an environment free from judgement
  • train surgeons how to use new or unfamiliar devices
  • presenting medical images such CT-Scans and MRIs as 3D renderings for improved accuracy of diagnosis 
  • and as an alternative treatment for seniors

4 Blockchain 
Interoperability in Healthcare is a big topic for debate and a sore unsolved puzzle. With the US HHS and ONC seeking research on Blockchain for Healthcare, there seems to be growing interest in the technology. 

For instance, “By combining the blockchain with the peer-to-peer business model, this creates the potential for a near-autonomous self-regulated insurance business model for managing policy and claims. No single entity would control the network. Policyholders could “equally” control the network on a pro-rata basis” 
– Cyrus Maaghul in Why out of hospital Blockchains matter

Blockchain technology is being researched to be the super secure healthcare data aggregator of EHR data and IoT devices data

Blockchain technology is supposed to benefit healthcare 

  • in population health and clinical studies, 
  • interoperability, 
  • patient centricity, 
  • security,
  • supply chain management 
  • Merck has already announced its exploring the use of Blockchain technology for clinical trials. For instance, if a patient is enrolled for multiple clinical trials, a single blood test common to all the clinical trials needs to be done only once and can be shared across the clinical trial studies the patient has enrolled for.
  • In a recently concluded challenge, ONC in the US announced 15 winners for the use of Blockchain in Healthcare

5 Artificial Intelligence
Artificial Intelligence has been a topic of research all these years, but with the advent of the Data Age, Artificial Intelligence is fast moving mainstream and presents a viable business opportunity. 

“By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries.” — Harpreet Singh Buttar, analyst at Frost & Sullivan.

In a recently published report, AI adoption by enterprises is imminent. 38% of respondents are already using AI, another 28% will adopt it by 2018. 

The AI ecosystem is projected to be worth $5.5Billion by 2020

Artificial Intelligence ecosystem consists of:

  • Deep Learning
  • Evidence Based
  • Machine Learning Systems
  • Prescriptive Analytics
  • Natural Language Generation
  • NLP/ Text Mining
  • Predictive Analytics
  • Recommendation Engines

Artificial Intelligence has already started making its way into healthcare, with 90+ AI startups getting funding to deliver solutions like; 

  • helping the oncologist define the best treatment plan specific to each patient
  • a virtual nursing assistants, to follow-up with patients post discharge
  • drug discovery platforms, for new therapies
  • Medical Imaging and diagnostics 
  • The use of AI in diagnosing diseases, patient education and reducing hospital costs
  • You can also find a great discussion on machine learning, wherein how machine learning could replace/ augment doctors via the health standards podcast with Fred Trotter.

Some of the other areas where AI is being implemented in Healthcare. Microsoft, Apple, IBM and other major players are all looking to AI help in curing people. And they are forming a group that creates the standard of ethics for the development of AI.

Finally have a look at the AI in healthcare: Category Heatmap

Source: CBINSIGHTS


6 3D Printing 
3D Printing in Healthcare is making fast inroads in many disruptive ways. The projected market size for 3D Printing in Healthcare as suggested in the IDC report:

“Global revenues for the 3D printing market are expected to reach $US35.4 Billion by 2020, more than double the %US15.9 Billion in revenues forecast for 2016.

This represents a compound annual growth rate (CAGR) of 24.1 percent over the 2015-2020 forecast period, IDC research reports that while 3D printers and materials will represent nearly half the total worldwide revenues throughout the forecast, software and related services will also experience significant growth”

Gartner expanded the number of profiles from 16 in 2014, to 37 technology and service profiles in their latest Hype Cycle for 3D Printing 

3D Printing in Healthcare is being used in the following ways: 

  • 3D Printing and Surgery. All surgical and interventional procedures with complex pathology, extensive resection and/or extensive reconstructions could benefit from this technology: Orthopedics, Cardiovascular, Otorhinolaryngology, Abdominal, Oncology and Neurosurgery.
  • A bespoke 3D Printed model of the patient’s forearm changed the standard course of a 4 hour surgery to a 30 min less evasive soft tissue procedure
  • Affordable prosthetics
  • the FDA has touted the use of 3D Printing in personalised medicine, ans has already cleared 85 medical devices and one prescription drug manufactured by 3D Printing.

Researchers are also exploring the use of 3D Printing which could come mainstream in the future such as Printing prescription drugs at home, Synthetic skin, 3D Printing and replacing body parts.

7 Drones

Last year in a conference a researcher proposed the use of Drones for delivering healthcare in much the same way Katniss receives medicine in the Hunger Games movie or for that matter in the movie Bourne Legacy, UAVs are shown to retrieve the blood samples of Jeremy Renner.

The worldwide market for drones is $6.8 billion anticipated to reach $36.9 billion by 2022

Similarly, there is an active interest in the use of drones to be monitoring traffic, to delivering pizza and products ordered online. 

In context of Healthcare, UAVs are being field tested for transporting samples and blood supplies, medical drone manufacturer Vayu is using UAVs to deliver cutting edge medical technology in Madagascar. In Rwanda, estimated 325 pregnant women per 100,000 die each year, often from postpartum hemorrhage. Many of these deaths are preventable if they receive transfusion via drone delivery in a timely manner. 

In India, Fortis hospital plans on using drones during Heart Transplants, to cut the travel time and save lives. An estimated 500, 000 are in need for organ transplants in a year in India.

Drones & UAVs are also being tested for delivering emergency medical supplies during accidents and natural disasters.

8 Robotics

Robotics in healthcare has been used for sometime now, for instance the Da Vinci surgery system is being used for a myriad of surgeries. 

Just the other day i came across an article on robots being used for some of the tasks at the reception of the hospital.

“Cloud robotics can be viewed as a convergence of information, learned processes, and intelligent motion or activities with the help of the cloud,” the report explains. “It allows to move the locus of ‘intelligence’ from onboard to a remote service.”Frost and Sullivan report on Cloud Robotics.

The overall world market for robotics in healthcare will reach $3,058m in 2015, and expand further to 2025.

The global robotics industry will expand from $34.1 billion in 2016 to $226.2 billion by 2021, representing a compound annual growth rate (CAGR) of 46%.

I was reviewing the articles on Robotics in Healthcare and came across this very comprehensive article Robots/ Robotics in Healthcare by Dr. Bernadette Keefe, MD which provides a comprehensive look at the current and future trends.

Other areas robots are being used in healthcare in addition to the above scenarios are: 

//platform.twitter.com/widgets.js

Forrester’s Top Emerging Technologies To Watch: 2017-2021 http://bit.ly/2dmVRkZ  via @GilPress

And there you go, we look forward to you sharing your experiences and thoughts regarding these Future Technologies and share them with our community of readers. 

We appreciate you considering sharing your knowledge via The HCITExpert Blog

Suggested Reading

  1. The Future of Healthcare Is Arriving—8 Exciting Areas to Watch | Daniel Kraft, MD | Pulse | LinkedIn http://ow.ly/KrGS304kGjs
  2. Why the A.I. euphoria is doomed to fail | VentureBeat | Bots | by Evgeny Chereshnev, Kaspersky Lab http://ow.ly/CMKu304kGyU
  3. Looking Back At Today’s Healthcare In 2050The Medical Futurist http://ow.ly/4Dl6304kVZZ
  4. Incisionless robotic surgery offers cancer patients better chances of survival: StudyTech2 http://ow.ly/gpMS304l3wq 
  5. Robots/Robotics in Healthcare | Bernadette Keefe MD http://ow.ly/wRbb304lz44
  6. By 2020, 43% of IT budgets will be spent on #IoT: Jim Morrish, Machina ResearchThe Economic Times http://ow.ly/VKuT304lFi9  
  7. Forrester’s Top Emerging Technologies To Watch: 2017-2021 http://bit.ly/2dmVRkZ  via @GilPress
  8. Are killer bots about to do away with smartphone apps? – http://www.bbc.com/news/technology-37154519 
  9. Where machines could replace humans–and where they can’t (yet) | McKinsey & Company http://ow.ly/v9BY100dNn6 
  10. 2016’s hottest emerging technologies | World Economic Forum http://ow.ly/Jq2R100m4AS 
  11. The Top 10 Emerging Technologies 2016list, compiled by the Forum and published in collaboration with Scientific Americanhttp://www3.weforum.org/docs/GAC16_Top10_Emerging_Technologies_2016_report.pdf 
  12. Rwanda’s hospitals will use drones to deliver medical supplies http://money.cnn.com/2016/10/13/technology/rwanda-drone-hospital/index.html?iid=hp-toplead-intl 
  13. 4 Trends Shaping The Future Of Medical Events https://t.co/rUUUJ7oqkK #digitalhealth #hcsm https://t.co/KuPgGW4k9Z 
  14. Post-PC Tech Rules at Intel Developer Forum 2016 https://lnkd.in/fKux3Ek 
  15. House MD vs Doctor #AI- Who will turn out to be the better by @RoshiniBR http://ow.ly/elXy304mYpv

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    @IFTTT you could in Healthcare by @msharmas


    Was reading this article published in a leading newspaper sometime back,

    Naturally, I tried thinking of usecases to apply the technology in a Healthcare setting. 

    About IFTTT
    IFTTT works with a series of simple recipes using channels.  

    IFTTT stands for IF this then that

    Channels are “connected” apps, like Gmail, Google Calendar, Google Contacts, Twitter and many others supported by IFTTT. You can download IFTTT for android or iOS and start connecting channels to your account.  

    Recipes
    IFTTT allows you cook up your own recipes. Recipes are composed of this and that. Once you have connected the apps to your IFTTT account, you can start creating recipes. 

    “this” in the recipe stands for a Trigger Condition or criteria, much like the IF condition you would create in an excel sheet, or in code.
    “that” is the action that would be performed when the Trigger condition is met. Based on this condition being TRUE, IFTTT will execute that Trigger Action.
    Lets take an example now, assume you are attending a conference and you would like to keep a list of tweets that you liked, and you want to retweet these out later or incorporate these in a blog. Given this scenario, you could do the following steps in IFTTT

    1. Download the App on your phone and create an account
    2. In the IFTTT app enable the Twitter & Google Drive “channels” by connecting to your Twitter and Google Drive credentials
    3. Once you have connected the channels, lets head over to Create a recipe
    4. Click Create recipe and it will ask you for a Trigger Channel, select Twitter
    5. Next, select the Trigger Conditions from the list of possible options provided by IFTTT based on the channel selected
    6. For our usecase we will select “New Liked Tweet by you” as the Trigger Condition
    7. Next we want IFTTT to save the “Liked” tweet in an excel file, for that we will select the trigger Action channel as Google Drive
    8. And we will select the Trigger Action as “Add row to spreadsheet”
    9. IFTTT will keep adding all the tweets you liked to the spreadsheet that you have selected

    IFTTT you consider Healthcare Use cases 
    OK, so we now have some understanding and agreement in terms how we are able to very simply, and with no coding, able to create a logic statement and get some work done. In fact you have just “Integrated” two apps and got them to “interoperate”

    Lets now assume, IFTTT you could use in Healthcare use cases, What would you do?

    What IFTTT offers is a set of features that allows for the end-user to create some of the rules based on their day-to-day circumstances. Lets say a nurse wanted the EHR system to Alert a doctor based on a certain specific parameter, but incorporating that logic would require a “code-change” to be done by the EHR vendor. The process is long-drawn to bring in such changes. 

    Instead IFTTT the EHR system can incorporate the ability for the nurse to create her own recipe by providing Channels corresponding to various modules in the EHR system, and also provide the end users Trigger Actions  and Trigger Conditions (pre-defined by the EHR vendor).

    Lets consider some of the usecases that can be enabled for an IFTTT type functionality in Healthcare

    • appointment reminders for doctors based on urgency of care
    • reminders to the nurse to change patient medication dosage based on doctors suggestion of lab results
    • pharmacy requisitions based on quantity on hand value defined
    • checking and validating medical actions for medical errors
    • patient discharge process alerts to all departments


    IFTTT app allows for the end user to create her own “recipes” and “share” these within the community. And considering every patient’s treatment circumstances are different, clinical teams can setup trigger and action criteria that are active for a particular patient and can be continuously changed based on patient condition. Additionally, it also provides the end-user the ability to make enhancements to the system’s in-built logic by enabling customisation at the user end and instantaneously.

    Once the patient gets discharged the clinical staff can have the ability to save all the tasks related to similar disease “patients like” scenario, to be templated for future
     

    IFTTT you could Connect Healthcare Devices
    Thinking a bit ahead to the future, one could control certain medical devices based on trigger based activities. So imagine, the nurse comes along with the doctor for the ward rounds and she is able to adjust the IV flow based on a doctor’s recommendations

    IFTTT patients’ could

    Patients too can be allowed to use IFTTT-like functionality by allowing them to create a folder in her google drive that contains all her electronic records emailed to her or her doctor

    Patients can also setup reminders for their appointments since their hospital app enables the IFTTT-like functionality.
     
    Patients can be sent alert notifications on their wearables or phones, about daily Medication reminders using IoT-based devices that dispense their medications

    The power of IFTTT is in the simplicity and custom trigger and action criteria it provides it’s users

    While writing the above article I recalled the time I was working in a Healthcare IT Product development company in Bangalore and we were looking to incorporate an Alerts & rules engine into our HIMS product. While defining the requirements for the solution, we had discussions with our end users in terms of how they would like the notifications from the system to be delivered. They all reported “Alert Fatigue” to be a factor in terms of how they went about using the system. They wanted to be able to control what alerts they saw and how they would like to view these alerts. 

    An IFTTT-esque functionality incorporated within EHR systems will go long way in helping the end-users “customise” the solution based on their current requirements. They would be able to create focussed alerts based on their daily work. 

    Afterall, the workflows in the hospital undergo a constant change and an EHR should be able to allow the end-users to incorporate customised workflow and rules

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    Social Media Technographics – A way to engage your audience by @msharmas

    “Taken together, the Social Technographic groups make up the ecosystem that forms the groundswell. By examing how they are represented in any subgroup, strategists can determine which sorts of strategies make sense to reach their customers.” – Forrester


    As part of a successful social media campaign, its important to know the audience with whom we are sharing the content and creating the content for. 

    I came across this insightful categorization from Forrester, that provides a categorisation of your Social Media users, using the Social Technographics ladder on the basis of their level of activity on your Social Media Channels

    To enable an engaging social media strategy, it will be important to guide your followers across the various steps in the ladders, leading them from being Inactives to being Creators of thought leadership content.
     

    By examining each sub-group, social media strategists can determine which sorts of strategies make sense to reach their target customers. Companies that can understand the typography of their end customers can therefore better target their audience with topics and articles of relevance.

    Based on the Forrester Social Technographic ladder of engagement, the people participating and engaging with your content has been categorized by Forrester with the percentage for each type of person.



    Suggested Reading

    1. Forrester: Consumer Technographics https://www.forrester.com/data/consumer/dashboards
    2. Forrester: Consumer Technographics https://www.forrester.com/data/consumer/reports 
    3. How To Create A Social Media Marketing Plan In 6 Steps http://ow.ly/USsyb 
    4. The Data Digest: Twitter And Social Technographics by Reineke Reitsma | Forrester Blogs http://blogs.forrester.com/market_research/2010/01/the-data-digest-twitter-and-social-technographics.html
    5. The Data Digest: Introducing Forrester’s Empowered Customer Segmentation http://blogs.forrester.com/anjali_lai/16-07-12-the_data_digest_introducing_forresters_empowered_customer_segmentation 
    6. The Social Marketing Playbook For 2016 https://www.forrester.com/The+Social+Marketing+Playbook+For+2016/-/E-PLA124 

    How do you plan on using this categorization for your Social Media Strategy for your own brand? I look forward to hearing back from you with your thoughts and insights.

    We are using the following interactive Word Cloud to understand the conversations our readers are having around Digital Health topics

    https://www.infomous.com/client2/?width=700&height=450

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    #Interoperability the Missing Link for #DigitalHealth Apps by @msharmas


    In India we have 204.1 million smartphone users in 2016 [ http://www.statista.com/statistics/467163/forecast-of-smartphone-users-in-india/ ], it’s only natural to find startups using the mobile as the way to acquire customers by providing mobile Health based products and services.

    While it is a great way to provide accessibility and affordability of healthcare services via mobile health solutions, it is also important to understand the need to ensure interoperability of the healthcare data being captured in these apps.

    Today we have apps for Diabetes Management, Appointments Scheduling, Continuous Monitoring, Remote monitoring, Activity monitoring linked with wearables, women and child health, cardiology, telemedicine, secure messaging apps, etc. The list in the past couple of years has really grown exponentially. And that is great, since the mobile phone has become the centerpiece device for most people.

    One aspect seems to be missing in the Go-to-Market rush,
    >>  INTEROPERABILITY !!

    It reminds me of the scenario in healthcare regarding medical devices, which traditionally were never developed for the purpose of sharing data with other systems or outside the location they were placed. It just sufficed that they were connected to the patients and displayed the readings the doctor viewed during her rounds.

    And I find the same happening with the DigitalHealth Apps.

    I have been following some of the DigitalHealth Startups that have developed apps that cater to one specialty or another, and I have come across most of these mHealth apps to be trying to build in the feature-set, i.e., to be a patient’s one stop shop for healthcare related data. In doing this they are duplicating the patient health record and there is a speciality-specific personal health record in each mHealth App (just like the medical device).

    Since, each of the mHealth apps’ provides a feature for the patient to upload and store their records, soon we will have more “silos of information” than ever before. Multiply that with the number of apps a single user might have on her phone for capturing one or the other healthcare related parameter, the problem compounds.

    The problem of solving the interoperability of patient information will continue to be an area of concern.

    Its therefore very important for the startups developing mHealth apps, to start the app development process by incorporating the Interoperability Standards in healthcare. I think this should be the first step in the app development process and in fact patients and the healthcare VCs, investors should demand the app to have the ability to generate interoperable medical records out-of-the-box. The question that one should ask before downloading and using an app should be, “Will I be able to share my medical data between apps, in a Standard and interoperable form?”

    Quality & Interoperability

    Just as there is no compromise on quality, there should be no compromise on interoperability

    Take for instance the medical devices, no one insisted on interoperability, or the cost of enabling interoperability was perhaps higher than the cost of the machine, that no one went for it. It was perhaps thought, its OK, anyways the doctor goes on her rounds she will see the information

    Similarly, today if we take a ‘share-it via app way’ out to interoperability, we will not have demanded for the “right way” of doing things, we would simply have been taking the same approach as before.

    Interoperability should be a plug’n’play option and not a separate service that the vendor chooses to provide, if paid for. It should not be a “Optional”, or paid add-on.

    Last i checked there were 100,000+ “medical apps” on the various app stores. How many of these are interoperable? If earlier we had to contend with medical devices that were not plug’n’play interoperable, today we have siloed data being created by mHealth apps.

    Solutions to the Problem

    The EHRs should have the ability to “add” apps data to the patient EHR allowing for incorporating the mHealth App Data into the patient’s longitudinal record.

    The app developers should consult doctors and capture “contextual” healthcare data of the patient. The app should have the ability to share this data via the HL7 certified, interoperable document.


    Additionally, when a mobile user deletes a mHealth app from her device, any data stored for the patient should automatically be sent to the patient’s registered email as a HL7 enabled document. Providing a summary and detailed medical record information of the patient. These should be downloadable into any EHR or another app. 

    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 [Updated: 29th May 2016]
    Author

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    Manish Sharma

    Founder HCITExpert.com, Digital Health Entrepreneur

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