Month: July 2016

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
  2. Forrester: Consumer Technographics 
  3. How To Create A Social Media Marketing Plan In 6 Steps 
  4. The Data Digest: Twitter And Social Technographics by Reineke Reitsma | Forrester Blogs
  5. The Data Digest: Introducing Forrester’s Empowered Customer Segmentation 
  6. The Social Marketing Playbook For 2016 

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


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#Infographic: Technology Innovation in Public Health, Learning from INDIA via @InnovatioCuris

Infographic Source: Reaching the unreached through Technology Innovation in Public Health Learning from INDIA, Dr. Sanjiv Kumar & Dr. V K Singh –

Infographic Source

We came across a great presentation on “Reaching the Unreached Technology Innovation in Public Health – Learning from India”, via the webinar conducted by Dr. V K Singh along with Dr. Sanjiv Kumar. 

In the webinar, Dr. Kumar discussed how Policy and  Technology Innovations can be used to reach the entire population of India for delivery of Public Health Services. 

He spoke about the need to Identify and scale Innovations in India. Dr. Kumar highlighted different ways by which this is being done: 

  • States encouraged to include innovation in Program Implementation Plans
  • National Summits on Good and Innovative practices
  • National Health Innovation Portal –
  • Health Technology Assessment Workshops

We have prepared the Summary Infographic of the webinar conducted by Dr. Sanjiv Kumar & Dr. V K Singh, MD, InnovatioCuris and present it here for your reference.

In this webinar, we came across an interesting term, “Indovation” (“Indian Innovations”) used by Dr. VK Singh, while taking about not only learning best practices from across the world, but also have the ability to share the “Indian Innovations” in solving the problems of accessibility, affordability and scale in deliver of Public Health 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


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#INFOGRAPHIC: India’s Unique Challenges in Healthcare Delivery by @iamGuruprasadS

Information sourced from

The Infographic based on talk India’s Unique Challenges: An Opportunity to Innovate? by Guruprasad S, GM, Healthcare Practice, Robert Bosch Engineering & Business Solutions


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3P’s framework to be Successful by Prashantha Sawhney

All of us look for formulas to climb the ladder of success, we can either invent our own or leverage what others before us have tried. Every industry has well documented practices, frameworks and standards that provide guidance on how to be plan, execute and be successful.

The one framework that has appealed to me and been found useful is called 3 P’s. These are 3 equal pies that help make the circle of what is required to be successful. 

  1. People – relates to “who” does the work
  2. Process – relates to the “how” the work is to be done
  3. Product – relates to the “why” and “what” work needs to be done


Many engineers/ technical/ functional experts sometimes tend to think of this aspect as being HR/managerial related. However this is a really critical part as this is the group with whom we spend most of our waking hours. Without people (whether it is 1 or 100 or 1,000), the wheel cannot exist. It is not just about having people occupying seats, but about having the right people. Having people collaborate with each other helps move in the right direction else there is no tangible progress.


Having appropriate processes in place helps us be predictable in what we do as well as enabling quality aspects to be met in a timely manner. We do not have infinite time, resources or money to try to do things the right way and need to deliver or execute in more defined ways with proper definitions of expectations at each stage of the process. These can evolve or time and get overly complicated but with right attention they can also be simplified Execution cannot be as stated below:

The infinite monkey theorem states that a monkey hitting keys at random on a typewriter keyboard for an infinite amount of time will almost surely type a given text, such as the complete works of William Shakespeare. 


This is the end result that shows what we wish our customers/partners to use. It may be a tangible physical product, Software UI/Mobile App or maybe even just background API’s, but it needs to have a defined state when it can be considered complete. We may think of just being related to specifications of functionality, but it goes beyond that to understand why the product should even exist or is needed.

In short among other things, to be successful we need people who are skilled and motivated, who follow the processes and believe in the product they are working on.

More on each of these aspects in subsequent posts.

The article was first published in Mr. Prashantha Sawhney’s LinkedIn Pulse post. The article is reproduced here with the authors permission. The views shared by the author are shared in his personal capacity.
Prashantha Sawhney

Results-driven engineering professional with ~17 years of experience in leading high performance product teams

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

In India we have 204.1 million smartphone users in 2016 [ ], 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,

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]

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Can the Internet of Things #IoT transform Healthcare? by @drvikram

Internet of things continues to dominate the world apparent by the success of the Liveworx16 that recently concluded in Boston. Liveworx is the signature event of Thingworx a PTC company. The event saw a curious mix of CAD/CAM experts who were trying to understand how IoT was going to help them mingling with IoT experts who had already implemented a few projects and were looking to consolidate on their early mover advantage. But one Industry that is looking at IoT very seriously is healthcare. Yes you heard me its healthcare, and may even leapfrog other industries when it comes to IoT adoption.

But then why should healthcare look at IoT?

Well that is a good question that is being asked by many hospitals and rightfully so. Hospitals have a duty towards their patients, community, physicians and staff and the last thing they want to do is to embark on a new technology for the sake of technology. But before we look at why IoT, we should probably try to understand the origin of IoT.

Some might argue that IoT is not new, maybe the patenting of the passive RFID in 1973 was the origin of IoT. By the 1980’s many manufacturing units were already connected. Some others like consumer goods were using a form of IoT. For example Coke was using a similar technology with its vending machines in 1980’s which was invented at the Carnegie Mellon University. 1980 was also the year CERN launched World Wide Web (WWW) and the internet was born. By 1990’s Wal-Mart had mandated all organizations that are displaying their goods to have advanced RFID chips. This had led to the famous spat between P & G and Wal-Mart. I am not sure who blinked first but for a while P & G was off the shelves at Wal-Mart.

By 2000’s we started connecting devices to the internet. Power grids and Energy companies started systems which were talking to each other. Soon cell phones were connected and then by 2008, we saw the inflection point on the number of connected devices. Today we have wearable devices that can send your physiological data to your physician that can help him or her track your health parameters like BP and sugar levels.

IoT in India is not new either. I know for example a hospital in Delhi-NCR region had ambulances with antennas on its top, ECG machines, and monitors along with physicians in the ambulance. This way despite the traffic jams in India, the critical records of the patients would arrive at the ER and the physicians and surgeons would make the necessary preparation for stabilizing the patient and save valuable time that otherwise they would have wasted in these tests. At that time Rajesh Batra who was head of technology, was able to make this work and get the physicians and management on board by demonstrating the value of IoT in an ambulatory set up.

“IoT has the potential to improve care” says Rajesh Batra , “But we need to be careful about security as it very easy for a breach which would be dangerous for a hospital”

He continues the same zeal in Kokilaben Hospital in Mumbai where he currently is the CIO. He is also looking at integrating IoT with emerging areas like Omni Channel with iBeacons to give a truly connected experience at the hospital.

As I have written many times in the past, we in India have this unique opportunity to create a new healthcare model that can help 1.3 billion people manage their health. I think an important component of that is population health.

Now a hypothetical population health program could work on the principle of a hospital enrolling a set of patients who need chronic care, let’s say for example diabetes into a program. The program entails these patients to check their sugar levels regularly and through IoT their sugar levels get updated into a program dash board that the physician can see. If the sugar levels are within the parameter then there is no incident. But if the sugar levels rise or fall outside of the normal range. Then the system alerts the physician. The physician would check if this is one off case or is there is a regular pattern. Based on this he or she can intervene and schedule a checkup and enter the same in the record.

Now this is a simple example, but helps us to understand how a potential IoT solution could work in population health. It would not only help in tackling chronic diseases in India, but could serve as the only option in tier 2 and tier 3 cities where access to hospitals is not available. Having said all that IoT will definitely shape the future of healthcare in the country, the only thing to be seen is the extent of that transformation.

The article was first published on Dr. Vikram’s Blog, it is reproduced here with the authors permission
Dr Vikram Venkateswaran

Dr Vikram Venkateswaran is a healthcare thought leader who writes and speaks about the emerging healthcare models in India and the role technology plays in them.

Benefits of an AI-Based Patient Appointments service for Hospitals by @msharmas

One of the areas where AI can be implemented in the Hospital with high volume of transactions, is the Appointments Scheduling of Patients. On any given day, there are a finite number of slots available for a doctor, e.g. 10 min or 30 min slots, depending on whether its a first visit or a follow up visit. In most hospitals, Routine patients are scheduled in advance and some patients are scheduled based on an urgency, to the physician schedule.  [Denton et al – 8]
A typical workflow for booking an appointment can go like this:

1. Patient calls (or visits) the hospital, and speaks to the person at the reception, at a specific department
2. The person looks up the available time slots, that a doctor is free and available in the clinic
3. Consults with the Patient on the best time possible for her appointment and then schedules the appointment

Now this three step process can either happen on a call, at the hospital reception or via a website provided by the hospital. But in real life, the appointment booking process for a patient might not be so straight forward. Here are some of the different scenarios that might occur:

1. Doctor is not available, asks her medical assistant to cancel all her appointments. Existing appointments need to be shifted to other doctors or rescheduled based on patient priority.
2. Patient calls at the last moment and asks for her appointments to be re-scheduled or cancelled
3. Patient does not show up for the appointment, and asks for a new appointment
4. During a clinic day, multiple new and urgent cases need to be seen by the physician, which delay the subsequent appointments
5. Scheduling of renal therapy patients or cancer therapy patients also needs supervised scheduling that is closely related to the patients’ care protocols and care plans
6. Scheduling based on urgency and emergency situations also changes the “scheduled” visits of a doctor 
Considering these challenges in the daily working environment of a hospital, an AI-based scheduling solution can help the hospitals in providing an optimal use of resources. For instance a research from Indiana University [4] found using Artificial Intelligence in patient care can be cost effective and improve patient outcomes.

Consider for instance the following statistics of a Government Hospital in Rajasthan, India [6]:

  • Nearly 1.27 crore patients were registered at OPD in medical centres affiliated to medical colleges and
  • 9.27 crore in state medical institutions in the year 2014-2015
  • in the year 2015 around 35,000 patients per day were registered at the OPD at medical college-affiliated centres

The High number of patients (the 35,000 per day patients registered at the OPD at medical college-affiliated centres) and the resource scheduling scenarios, presents an apt usecase to implement an AI based Appointment Scheduling system.

While it not only present a challenge to manage the care of all the visiting patients, it also allows for the administration to ask; How many doctors, nurses and medical assistants should be scheduled to manage the care planning & scheduling requirements of each of these patients, visiting one or many departments of the hospital.

In addition to Patient Scheduling, AI based algorithms can be deployed in such settings [2] to help the hospital administration in optimising the time of their most important resources: Physicians, nurses and medical assistants.

Handbook of Healthcare System Scheduling – Reference [7]

Additional Scenarios where the AI based resource scheduling systems in Healthcare [7] can be deployed are:

  • Operating Theatre + Operating Team Scheduling
  • Renal Dialysis Centers
  • Radiology Diagnostic Facilities
  • Medication Reminders Apps
  • Acuity-based nurse assignment and patient scheduling in oncology clinics
  • Care Plans based activity & event scheduling
  • Procedure Scheduling
  • Health Checkups Packages

Once an AI based solution has been implemented, the scheduling, rescheduling, planning, allocating and many other scenarios are handled by an AI based Scheduling Agent allowing for hospital administrators and physician scheduling managers to focus on treating the patients. 

And Scheduling a patient appointment becomes an autonomous process:

A. Jane emails Dr. John to schedule an appointment for a followup visit. Jane receives a confirmation email regarding the appointment with Dr. John from his assistant Amy. A reminder is set in her calendar.

B. Jane, on the day of the appointment is unable to make it to the hospital and sends an email requesting for rescheduling her appointment to the next wednesday. Amy reviews, Dr. Johns schedule and responds to Jane with a confirmation of her re-scheduled appointment.

In the above example Amy is an AI assistant to the Physician, nurse or medical health professional. Or in fact it could be an assistant (Siri, cortana, or amy from etc) to the Patient.

What do you think, do share your thoughts?

Sundar Pichai, CEO, Google says we are moving from a mobile first world to an AI first world, quite fast.


  1. How to use AI to automatically schedule your appointments with – TechRepublic 
  2. [1206.1678] A Distributed Optimized Patient Scheduling using Partial Information 
  3. Artificial Intelligence in Healthcare: A Smart Decision? | Health Standards 
  4. Can computers save health care? IU research shows lower costs, better outcomes: IU News Room: Indiana University 
  5. Association for the Advancement of Artificial Intelligence 
  6. E-registration Facility Soon At SMS HospitaleHEALTH | EHEALTH 
  7. Handbook of Healthcare System Scheduling – 
  8. From Scheduling Meetings To Shopping Deals: 14 Early-Stage AI Assistants To Watch
  9. Who will turn out to be the better diagnostician? #digitalhealth #ArtificialIntelligence
  10. Robot Takes On Role Of Hospital Scheduling Nurse | Digital Trends
  11. This is how the future of hospital operations resembles air traffic control – MedCity NewsMedCity News
  12. Can Artificial Intelligence Help The Mentally Ill? #mentalhealth #AI
  13. On-line Appointment Sequencing and Scheduling – Brian Denton et al,
  14. Artificial Intelligence Can Improve Healthcare | EMR and EHR


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TRIVENI: A remote patient monitoring solution via @msharmas – Part 2

Introduction to Part 2

In the part 2 of this series, I will endeavour to define the Business Case and the Timelines for the Research and Development of the TRIVENI framework.

In putting across the Business Model Canvas, the effort is to present a case study for Medical Device development in India.

In this blog post I provide the details of the 9 building blocks of the TRIVENI: Business Canvas Model

In the concluding part of the blog, I will provide the Project Plan and effort estimates for developing the TRIVENI platform to cover the Research & Product Development Phase.

Suggested Reading

  1. Unlocking the potential of the Internet of Things | McKinsey on Healthcare
  2. 10 most in-demand Internet of Things Skills – CIO – Slideshow
  3. Analyzing Cost Structure for Medical Device Companies – Market Realist 
  4. Lantronix on “Why Every Healthcare Device Should be Connected to the Internet of Things” | Symmetry Electronics

SNOMED CT CSETS – Its Place and Use by @sbbhattacharyya

The Concepts related to CSets are as proposed by Dr. SB Bhattacharyya and presented in the HCITExpert Blog with permission from Dr. SBB –

What is a Constrained Set?

  • The word constrain means “to control or limit something” (Cambridge Online  Dictionary)

  • SNOMED CT makes extensive use of refsets (reference sets), for a wide-range  of purposes, each of which have specific purposes

  • Refsets need to conform to certain specific rules and guidelines regarding their
preparation, distribution and maintenance
  • Takes a long time to design one and the designing entity needs to have a
 namespace assigned to it
  • This makes the rapid and effective use of SNOMED CT in individual systems  cumbersome at best and impractical at worst

Solving this conundrum

  • Since within a system it is pretty much lassiez faire or “anything goes”, it is wise  to use a Constrained Set of the SNOMED CT that suits the purpose

  • For example, for gender or laterality, a small list specially created SNOMED CT code set for that purpose should work excellently (actual list follows)

  • Thus, wherever there is a requirement for a system to have a list presented to 
the user for their selection, this small list serves the purpose
  • This limited list is termed a “Constrained Set” or CSET (a portmanteau of the  two words that it refers to) by Dr Bhattacharyya

CSets for Gender & Laterality

(Created using Cliniclue®)

248152002 | female |  
248153007 | male |  
32570681000036106 | indeterminate sex |  
32570691000036108 | intersex |
407374003 | transsexual |

7771000 | left |  
24028007 | right |  
51440002 | bilateral |


  • This constrained list works very well and suits the purpose of helping users to  fill in the gender or the anatomical side

  • The format of expressions as per the IHTSDO construction rules states that  either of the following is acceptable (only pre-coordinated types are shown here)

    • ConceptID
    • ConceptID | Term|
  • Thus, let’s say, for “bilateral” laterality, either of the following works

    • 51440002
    • 51440002 | bilateral |
  • It is important to debate the merits and demerits of such an approach

  • Not only must the pros and cons be considered but also the end-result should
 justify it
  • For starters, let us briefly study the refset approach

  • It should be noted that refsets are meant to be exchanged with external  entities in their entirety and need to be updated after every release –  international or national

  • It should also be noted that by the term “system” it is meant any system that uses SNOMED CT


  • Namespace required if refsets are shared with external entities/systems

  • Needs regeneration after every release

  • Can be automated using pre-set scripts (e.g., SQL, Perl, etc.) that needs to be  designed in-house


Data Management

  • When data is managed, it is the expressions that are stored and exchanged

  • The expressions have a machine-processable part (ConceptID) and a human-readable  part (Term) of expressions or just the machine-processable part (ConceptID), it is  largely a system designing issue, which is an internal matter

  • Thus, system designers only need to consider that which is necessary to capture,  store, retrieve, display, exchange, processing and querying

  • Anything else is not related to the system functionalities

  • Refsets have largely a governance connotation

Comparing Refsets with CSets


  • Formal, Exchangeable

  • Not easily reproducible – needs  namespace

  • Needs to be adapted for system  use – cannot be used as-is for  data capture, storage, retrieval,  query and exchange


  • Informal, Non-exchangeable

  • Easily reproducible – does not  need any namespace

  • Ready-to-use for data capture,  storage, retrieval, query and exchange

Benefits of CSets


  • Quick to develop and ready-to-  use

  • Can design, create, deploy and re-use as per specific system  requirements

  • Needs a team with properly  trained and experienced  professionals to design and  create

  • Needs updating with every  release – international and national


  • Since most of the data is required to be captured in pre-coordinated expression forms  (the form as available from international or national releases) that is either ConceptID  only or ConceptID | Term | formats, the system designers need to have access to these  for storing in their databases and used as-is

  • For queries, transitive closure tables are required for data aggregation, else, either  only the ConceptID or only the Term need be used to return the proper records

  • The CSets are easy-to-create being mostly built on-the-fly and hardly taking more than  an hour to create moderately complex ones, provided the right domain experts are  available to guide the designers


  • A good SNOMED CT tool like ClinClue® or Snow OWL® is required

  • A terminologist would be ideal but it may be tough for system vendors to hire

  • The next best person to do this type of work is a health informatics professional who  familiar with SNOMED CT

  • Alternatively, the following may be considered as a team since this type of work
cannot be done by one person, it will be too error-prone and consequently risky
    • Someone familiar with the tool being used is usually acceptable

    • Someone well-conversant with SNOMED CT as a whole is required

    • A good DBA who can design the database in such a manner that duplicates are  removed – the way SNOMED CT is modeled, the same term may be present in  different hierarchies

    • A domain expert – specialist, doctor, nurse, dentist, paramedic, etc. – is  required to identify all Terms (preferred as well as synonyms) required for that  domain (clinical finding, procedure, disorder, allergy, etc.) to ensure that all  the necessary terms (both preferred and synonyms) have been incorporated

  • During system use, only the Terms are displayed while the ConceptIDs are  stored and/or exchanged with or without the Terms, with the Term to  ConceptID-to-Term mapping done at the API level
  • The best way is to identify the Term that best describes the domain concept  (marital status, laparoscopic procedure, lipid profile, etc.) and construct the  SQL statement that will extract all the necessary subtype children and  descendants, which will form the required constrained list of values

  • For maintenance purposes, rebuilding the CSets for every subsequent official  release of SNOMED CT, which happens every six months, can be automated by running these scripts to build a new CSet

  • The need to manually check the CSet does not go away though to ensure that  all the required concepts and their corresponding preferred terms as well as  synonyms have indeed been incorporated


CSets Types

Type A

  • Separate tables for each domain  item like Gender, Employment  Status, Drug & Medicament,  Absence findings, etc.

  • No CSetID needed

  • Easy to build and maintain

  • Requires regeneration of separate  tables with every release –  several run cycles

Type B

  • One table where every domain is  uniquely identified through CSetID that is self-determined and self-generated

  • Complicated to build and maintain

  • Requires running several scripts  in series that populates and updates a single table with every release – automated single run cycle


  1. Matter based on ideas formulated by Dr SB Bhattacharyya
  2. Some matter sourced from presentations prepared by Dr Karanvir Singh in
 consultation with IHTSDO on behalf of National Release Centre, India
  3. IHTSDO –
  4. National Release Center, India – 
  5. What is SNOMED CT –

The Concept related to CSets are proposed by Dr. SB Bhattacharyya and presented in the HCITExpert Blog with permission from Dr. SBB.


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Dr. S B Bhattacharyya

Digital Health Influencer, Medical Doctor with experience in the healthcare industry in the fields of clinical practice, hospital administration, and medical informatics with particular focus on clinical data analytics.

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