Tuesday, 29 November 2016

Patient Satisfaction: IoT Enabled patient pathway by Arnab Paul, @iArnabPaul

They may forget your name, but they may never forget how you made them feel... Maya Angelou

Patient satisfaction is not a clearly defined concept, although it is identified as an important quality outcome indicator to measure success of the services delivery system

Ever since the Institute of Medicine’s 2001 'Crossing the Quality Chasm' report codified patientcenteredness as one of six health care quality aims, patient-centered care has gained footing within the landscape of health care reform. There is no consensus between the literatures on how to define the concept of patient satisfaction in healthcare. In Donabedian's quality measurement model, patient satisfaction is defined as patient-reported outcome measure while the structures and processes of care can be measured by patient-reported experiences

Many of our Linkedin friends would concur that even if we run a million dollar enterprise and have a fairly good experience on dealing with stressful situations in our everyday business life but when it comes to visiting the hospital we get cold feet – because of the element of unforeseen and unexpectedness of the entire process that we have to undertake and on top of that we as a patient community do not have a collective voice and it makes matters worse.

I believe we have a tremendous potential as a nation provided that we as a provider and receiver of healthcare services are on the same page, though it is easier said than done.Patient who visits a hospital is looking for value on investment (VOI) and the Provider is looking for return on investment (ROI). Healthcare providers have their limitations, financial and otherwise --- but at least they are doing their bit and performing reasonably well. Since they have fixed resources at their disposal – the only thing humanly possible for them is resource optimization.

In India, we have already missed the bus when it comes to patient satisfaction surveys unlike our western counterparts. For everything in life we need some kind of metrics, some tools to measure the clinical outcome and the patient satisfaction. So to make up for it may I suggest we incorporate Tech enabled, IoT optimized patient feedback mechanism.

Various Accreditation bodies like NABH, NABL, CAP, JCI and ISO are functioning in the healthcare domain but these are mostly voluntary, these accreditations are a reflection that the entity has undergone high quality of audit in its internal departments, but does it say anything about the patient satisfaction or patient engagement, the answer is a big NO. In India, one could safely bet that 90% of the patients visiting the hospitals do not have the foggiest notion of what do these accreditation means, entities need to think beyond certifications and accreditation, entities need to educate people, create more awareness among the stakeholders specially the patient community, they ought to let the world know that these organizations have the benchmark this will inspire confidence in the patient community.

So in a truly democratic healthcare system the patient ought to have a voice and a mechanism in place just to ensure that his voice his heard and above all accreditation agencies must also factor in the patient voice.

Few days back I got a very interesting email from someone who heads the ‎Clinical Transformation and Analytics, Clinical Technology and Patient Safety Innovations at a Super Speciality, New Delhi, she enquired about the tech solutions that could be put in place to enhance the patients positive experience,it so heartening to note that the providers are seriously interested in improving the patients experience and by and large I presume most of the providers do want to improve the patients experience.

So what is the solution, how do we propose to go about it, well unlike Press Ganey & HCAPHS, I don’t know of any organization in India working towards the goal of providing patient satisfaction survey. Press Ganey has stated that a minimum of 30 survey responses is necessary to draw meaningful conclusions from the data it receives and that it will not stand behind statistical analysis when less than 30 responses are received. The entities mentioned above are highly detailed paper based patient feedback mechanism, in this time and age we need to think digital, think ahead.

If we go digital & truly real time in the patient feedback mechanism it would greatly enhance the whole patient experience and maybe help to manage solve some of the issues in real time. Wouldn’t it be just great if we incorporate IoT’s in the patient feedback loop, we wouldn’t have to wait for 30 odd surveys to be analyzed we could just go ahead and fix the situation right away if it warrants an action. 

The article was first published in Mr. Arnab Paul's LInkedIn pulse page, it has been re-published here with the author's permission
Author

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[content title="About Arnab Paul"]
Arnab Paul, CEO, Patient Planet
Globally-minded systems thinker, action-oriented and inspired toward optimizing health outcomes through innovation, creativity, cooperation. Passionate about facilitating the alignment among technology, people and processes to ultimately improve patient experience and the functioning of healthcare.
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Monday, 28 November 2016

Shift in US Healthcare by Srinath Venkat, @ConnectSrinath

The adoption of EHR is growing rapidly because of billions of dollars spent by the government to incentivize providers for EHR usage.
Also, there is a greater commitment by government to reduce the drug related adverse events in healthcare by recommending e-prescribing to the providers

Transformation in US Healthcare through EHR and Personalized Healthcare
Healthcare has undergone series of changes in last few decades. From passive, reactive, one size fits all approach, it has moved towards more customized, responsive, real-time care administration. Electronic Health Record (EHR) is systematized longitudinal collection of patient health data which gives the complete record of clinician-patient encounter. 


It also streamlines the clinical workflow, thereby improving the health outcomes through decision support, quality management and reporting of information across the continuum of care. There are various vendors who provide EHR services based on the care setting (Ambulatory, Hospital, Clinic or Physician office), and the major ones include EPIC, Cerner, McKesson, Allscripts and GE.
 

The Health Maintenance Organization (HMO), which provides managed care by giving access to providers in its network for self-financed and insured individuals, were first started in 1931 by Farmer's Union of Oklahoma, where flat fee is collected irrespective of the services rendered. By 1951, it was estimated that 45% of the Americans were insured, and in 1965, Medicare which covers the older people above 65 years of age and younger people with disability was introduced. 

In 1996, Health Insurance Portability and Accountability Act (HIPAA) was introduced, which helps in protecting the healthcare information and reducing the healthcare administrative costs. In 2010, Patient Protection and Affordability Care Act (PPACA) was introduced which helped the people to purchase health insurance through Health Insurance Exchanges.
 

The Four Ps of Healthcare (Patient, Provider, Payer and Public) benefit from the EHR which helps in integration of healthcare information, reducing the duplication, avoiding redundancy, thereby reducing the administrative and treatment cost in healthcare. 

The Meaningful use of EHR is the usage of certified (Certification Commision for Healthcare Information Technology) health information systems and software for improving the health outcomes and reducing the cost. EHR has both provider and payer component. Doctors, Hospitals, Laboratories, Pharmacy and other ancillary services use provider systems, which includes, practice management, EHR, Revenue Cycle Management (RCM), Document management and E-prescribing. 

There is a shift in healthcare towards retail-like scenario leading the consumer driven healthcare, where the patient is well-informed and shops for different treatment options using web portals like Web MD. Remote medical practice, real-time data collection, information integration and transfer, and collaboration among providers using EHR, creates significant improvement in overall health outcomes and cost. 

The adoption of EHR is growing rapidly because of billions of dollars spent by the government to incentivise providers for EHR usage. Also, there is a greater commitment by government to reduce the drug related adverse events in healthcare by recommending e-prescribing to the providers. The shift from pay for volumes / pay per visit towards pay for performance / outcomes which is encouraged by creating Accountable Care Organizations (ACOs) is a motivational factor for meaningful use of EHR in healthcare.

The article was first published on Srinath Venkat's LinkedIn Pulse page. The article has been republished here with the authors' permission

Author
Srinath Venkat
Srinath Venkat is a Healthcare Management Professional with qualifications in Public Health, Healthcare Technology Assessment and Entrepreneurship in Emerging Market Economies. He has been in to research and consulting roles with leading healthcare research firms in activities like Market study, Go To Market strategy, Technology Mapping and Business Model evaluation. He is passionate about innovative business models, startup ecosystem and the evolving landscape.

Saturday, 26 November 2016

Putting patients at the heart of IoT in India, By Arnab Paul, @iArnabPaul

Patients are the most important stakeholders in the healthcare ecosystem and that they should be empowered to make informed choices.

In a broader sense, the "patient pathway" is the route that a patient will take from their first contact with a healthcare provider or a member of staff, through referral, to the completion of their treatment. It also covers the period from entry into a hospital or a Treatment Centre, until the patient leaves.

In healthcare, there already exists whole gamut of technologies in various states of maturity – wearable devices that are perhaps not yet ready to be used as clinical-grade, beta-versions of monitoring devices, inventory tracking systems already being utilized in hospital operations, etc. The innovations we will see in the coming years will push these to new heights and give health system operations the opportunity to be leaders in adoption of the connected world empowered by the internet of things. Willingness to explore the opportunities presented by this world will be the differentiator between those who leverage the capabilities for optimization and those who stick to what’s been just good enough so far.

Internet of Things (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. One area where the technology could prove transformative is in healthcare. The potential of IoT to impact healthcare is wide ranging. We've already seen an increasing movement towards fitness tracking wearables over the last few years. Imagine a world where your vital signs were being constantly monitored and fed back to your healthcare professional.

Many of us who advocate LEAN in Healthcare, we know that lean stands for removing all that is not required, Simply, lean means creating more value for customers with fewer resources. A lean organization understands customer value and focuses its key processes to continuously increase it. The ultimate goal is to provide perfect value to the customer through a perfect value creation process that has zero waste. The core idea of lean involves determining the value of any given process by distinguishing value added steps from non-value-added steps, and eliminating waste so that ultimately every step adds value to the process. To maximize value and eliminate waste, leaders in health care, as in other organizations, must evaluate processes by accurately specifying the value desired by the user; identifying every step in the process (or “value stream,” in the language of lean) and eliminating non-value-added steps, and making value flow from beginning to end based on the pull — the expressed needs — of the customer/patient. When applied rigorously and throughout an entire organization, lean principles can have a dramatic affect on productivity, cost, and quality.

With the deployment of IoT in healthcare it would enhance the scope of monitoring patients response, since huge zettabytes of data are going to be generated from the many monitoring sensors, if we are somehow able to remove the noise and work on the intelligence derived from it, and if we could somehow wed the intelligent data derived from IoT with the LEAN/ SIX SIGMA tools it would greatly enhance the quality of the patient care pathway. We would be able to do a better job of mapping his entire journey and improve on the patient e care pathway.

IoT in itself wouldn’t be a big help unless the information that is obtained from the sensors and other embedded systems are not synced with data analytics.

These are exciting times for Healthcare Delivery system, after proper deployment of sensors and by the optimum use of other remote monitoring system, suffice to say monetizing the data generated by the IoT would be the principle driver for enterprises and small businesses alike in years to come.

The article was first published in Mr. Arnab Paul's LInkedIn pulse page, it has been re-published here with the author's permission
Author

[tab]
[content title="About Arnab Paul"]
Arnab Paul, CEO, Patient Planet
Globally-minded systems thinker, action-oriented and inspired toward optimizing health outcomes through innovation, creativity, cooperation. Passionate about facilitating the alignment among technology, people and processes to ultimately improve patient experience and the functioning of healthcare.
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Medical Imaging Informatics Market by Swapna Supekar


Increase in number of diagnostic imaging procedures and high prevalence of chronic diseases spur the growth of medical imaging informatics market

Medical imaging informatics involves usage of digital technology to capture medical images, facilitating data analysis to record and correlate observations, and draws conclusions that play a vital role in the diagnosis of medical problems. The implementation of electronic health records (EHR) in the healthcare industry increases the demand for medical imaging to exchange medical images in the various departments of healthcare settings.

Increase in number of diagnostic imaging procedures and high prevalence of chronic diseases have raised the demand for various advanced diagnostic image processing and analysis software around the world. The healthcare industry focusses on developing procedures for early diagnosis due to rise in the number of chronic diseases, providing maximum growth potential for imaging procedures. 

For More Professional and Technical Industry Insights: 
https://www.alliedmarketresearch.com/medical-imaging-informatics-market

aAccording to the Organization for Economic Co-operation and Development (OECD), North America had an increasing number of imaging procedures for computed tomography (CT) and magnetic resonance imaging (MRI). For instance, in the U.S., 76 million and 81.2 million CT scans were performed in 2013 and 2014, respectively, representing an increase of around 7% from 2013 to 2014. Similarly, MRI scans of a total 1.78 million and 1.87 million were performed in 2012 and 2013, respectively, in Canada. 

Furthermore, Europe reported an increase in number of diagnostics imaging procedures. In Germany, positron emission tomography (PET) scans of a total 0.08 and 0.09 million were performed in the hospitals in 2012 and 2013, respectively. Thus, increase in the number of medical imaging procedures, rise in number of installations of medical imaging informatics, and high prevalence of chronic diseases worldwide are expected to propel the growth of the market.

Developed regions such as North America and Europe together accounted for the highest share in 2015 and is expected to maintain their leading position from 2016 to 2022, due to increase in demand for medical informatics technology, high adoption rate of technological advanced healthcare IT systems, well-established healthcare infrastructure, and presence of leading players such as Dell Inc., General Electric Company, Siemens AG, and others.

However, Asia-Pacific is anticipated to grow fastest during the forecast period, owing to large patient pools who require medical imaging procedures for the diagnosis of diseases. Moreover, increase in healthcare expenditure in the region and improving healthcare infrastructure are expected to support the growth of the market.n

The article has been published with the Author's permission

Author
Swapna Supekar
Swapna Supekar, is a keynote senior consultant on digital marketing at Allied Market Research. She has been recognized for developing a robust social network strategy for the company. Swapna has written several whitepapers, case studies, and articles. She is a visiting faculty member at various educational institutions and has expertise in life sciences and medical devices.

Monday, 21 November 2016

Challenges and Promise of #IoT in Healthcare by Arnab Paul, @iArnabPaul

A critical path to improving healthcare efficiency is to shift focus from acute care to early intervention. Remote patient monitoring technologies would be just a small cog in the wheel of Connected health


The ‘internet’ of people changed the world well there's a new internet emerging and it's poised to change the world again this new internet is not just about connecting people it's about connecting things and so it's named the Internet of Things.

Ok so connecting things to the internet big deal right well it kind of is and here's why because things can start to share their experiences with other things, you take things and then you add the ability to sense and communicate and touch and control and there you get an opportunity for things to interact and collaborate with other things so think of it like this, we as human beings, we interact and contribute and collaborate with other people in our own environment through our five senses we are seeing and smelling and in touch and taste and hearing, right well imagine things with the ability to sense and to touch and then add the than ability to communicate and that's where the internet of people and the internet of things intersect. I believe like the internet revolution, IoT opportunity is transformative. 

However there are few challenges   Some of the challenges that I can think of is like the interoperability issues of different software programs we do have an issue of  Heterogeneity of sensors and networks also last mile gap in delivering quality of service & Security with regard to  Privacy and Governance.

Broadly Challenges could be categorized under

Integration:  Gadgets & Devices
The diversity of devices in the networks is another obstacle for the successful implementation of IoT in healthcare.  The problem lies in the fact that the device manufacturers do not have an agreed-upon set of communication protocols and standards. The lack of uniformity among the connected medical devices also significantly reduces the opportunities of scaling the use of IoT in healthcare.

Security: Data Transmissions at risk
The main concern for regulatory bodies and users alike is, of course, the security of personal health information that is stored and transmitted by the connected devices. Strict access controls are required to ensure compliance with healthcare regulations.

Analytics : Data insights
Even though the process of collecting and aggregating data comes with complications, healthcare IoT is responsible for accumulating massive amounts of valuable data it can be used to benefit the patients, however deriving the insights from immense amounts of data is problematic without sophisticated analytics programs and data professionals.

A critical path to improving healthcare efficiency is to shift focus from acute care to early intervention. Remote patient monitoring technologies would be just a small cog in the wheel of Connected health. Health and fitness monitoring will precede patient monitoring as the driver for IoT solutions in healthcare. IoT in healthcare holds great promise for the coming generations because it could just transform the quality of life of the aging population. IoT could feel a bit intrusive  at times for the current generations, but looking at the trends it would help the millennials and the aging populations both get really helpful insight about the status of their health and act upon them.


The article was first published in Mr. Arnab Paul's LinkedIn Pulse post. The article is reproduced here with the authors permission.  
Author
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[content title="About Arnab Paul"]
Arnab Paul, CEO, Patient Planet
Globally-minded systems thinker, action-oriented and inspired toward optimizing health outcomes through innovation, creativity, cooperation. Passionate about facilitating the alignment among technology, people and processes to ultimately improve patient experience and the functioning of healthcare.
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Friday, 18 November 2016

3 P's framework - Product Motivation by Prashantha Sawhney

This article is the last in the series related to 3 P's framework to be successful. We finally focus on Product as it relates to the "why" and "what" work needs to be done.

Traditionally most people talk about products focusing on Feature - Function - Benefit methodology which has worked well for the past 40 years since it was introduced by IBM in 1976. With changes in times as well as proliferation of products, to differentiate their products, people also started to focus on USP (Unique Selling Proposition), RoI (Return on Investment), Efficiency savings, increased Effectiveness,  reduced TC (Total Cost of Ownership) etc. These are logical things which appeal to the mind, however many times we still are not able to decide on a specific product given this multitude of facts and figures.

This is where the Golden Circle from Simon Sinek comes in handy.  Focus is on moving from the Why to the What. It helps us understand the right way to reach our potential customers/partners and drives to deeper meaning on the very existence of the product.




The focus is now no longer just on the functionality that the product offers or how it achieves certain business objectives. With the clarity on why the product is needed, and with people who believe in the product, that brings in a good motivation for all involved parties and leads to eventual success.



PS: If you haven't watched his TED video (in the top 3 most watched videos on TED) - please do take some time to watch it and get inspired.

Do share your feedback/ views on other approaches you may have followed to be successful.

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

Wednesday, 16 November 2016

Healthcare IoT Strategy for Entrants & Incumbents by Arnab Paul, @iArnabPaul

The long-predicted IoT revolution in healthcare is already underway, as new use cases continue to emerge to address the urgent need for affordable, accessible care

We are still running around, jumping in the puddle of data mining and other data insights when we are hit by this new wave called 'Internet of Things" . Typically in the healthcare system the  patients dont really care what sensors will record and transmit and to whom and to where and whether it follows the standard protocol, what they really care about is whether they will be able to get well soon and how this IoT is going to help him have a better quality of life and how soon that would happen.  

Similarly the providers dont care about the tons of data that will be accessible to him, he would be more eager to know the intelligent real time information that would help him diagnose any ailment. However, at the moment, the health monitors, wearables remain largely outside typical care channels. 

One common IoT-enabled wellness monitor, for example, creates, transmits, analyzes, and stores data—but in a database not linked to, and incompatible with, traditional health records.  However useful, the information is unavailable or even unknown to doctors unless patients volunteer it—and, indeed, physically bring it to a visit. There is a gridlock in the flow of information at the aggregate stage. 

Alleviating that gridlock—and integrating prevention and wellness monitors with existing electronic health-records systems—is key to taking full advantage of IoT-enabled devices’ capabilities and keeping people healthier longer. Established health care IT companies, will no doubt find these new business models threatening, considering the new entrants eager to join the fight for customer value.  It is critical that IoT Companies deliberately identify how IoT technology fits into their existing products and strategies, and enables the delivery of transformational innovation. 

Simply using the IoT to enable innovation is unlikely to create sustainable advantage.  Companies should identify areas of high unmet needs and clearly articulate the value they will deliver for their customers. Development should begin with a specific use case in mind and a clear vision of how each stage in the Information cycle will contribute to addressing customer needs. Strategy to access capabilities through in-house development, acquiring companies, or partnering will be necessary. 

In all cases, whether entrant or incumbent, the IoT strategy should be built from an understanding of which care settings and which gridlock the entity seeks to alleviate.  From there, choices as to whether to focus on the setting or the stage of the gridlock will determine the appropriate business model. 

The long-predicted IoT revolution in healthcare is already underway, as new use cases continue to emerge to address the urgent need for affordable, accessible care. 

The article was first published in Mr. Arnab Paul's LinkedIn Pulse post. The article is reproduced here with the authors permission.  
Author

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[content title="About Arnab Paul"]
Arnab Paul, CEO, Patient Planet
Globally-minded systems thinker, action-oriented and inspired toward optimizing health outcomes through innovation, creativity, cooperation. Passionate about facilitating the alignment among technology, people and processes to ultimately improve patient experience and the functioning of healthcare.
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Sunday, 13 November 2016

Pragmatic #Interoperability by Dr. Charles Webster, @wareflo


"Pragmatic interoperability (PI) is the compatibility between the intended versus the actual effect of message exchange”

This article has been re-published with the authors permission. The article was first published by Dr. Charles Webster on his blog here

Healthcare is awash in data. We build messages. We send them. We parse them. We look up their meaning using nomenclatures, classifications, and terminologies. But health IT often fails to systematically do useful things with this encoded, sent, parsed, and looked-up data. We lack a sound theoretical foundation to our thinking about how to use healthcare data to communicate and coordinate human and machine action. I argue that this missing theory of interoperability is Pragmatic Interoperability.
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Issues of pragmatic interoperability manifest themselves as issues about coordination among EHR workflows (with and among other health IT systems). Pragmatic Interoperability is the science behind the practical engineering nuts and bolts in my previous 7000-word, five-part series, Achieving Task and Workflow Interoperability in Healthcare.

I will further argue that the most mature technology for implementing pragmatic interoperability today is workflow technology. Workflow technology encompasses a number of related technologies, from workflow engines, task and workflow management systems, business process management (BPM), and other process-aware information systems such as case management, interface engines, and customer relationship management systems. “Process-aware” means there is an explicit representation of work or workflow and engine executing or automatically consulting this representation of work during automated accomplishment or facilitation of work or workflow.

In many ways, the healthcare workflow, workflow technology, and workflow interoperability stars are aligning. There’s a great fit between BPM (Business Process Management) and FHIR (Fast Healthcare Interoperability Resources) when it comes Achieving Task and Workflow Interoperability in Healthcare. FHIR provides access to EHR data. BPM orchestrates tasks and workflows across EHRs and other health IT systems, potentially in different healthcare organizations. FHIR (and non-FHIR) EHR API (Application Programming Interfaces) initiatives will play an important role in ushering into healthcare the kind of process-aware BPM-style interoperable workflow it so desperate needs.

The key to achieving task-workflow pragmatic interoperability is representing clinical and administrative task and workflow states and events, and making them accessible via APIs. This is the necessary layer between data interoperability (syntactic and semantic, to be discussed below) and task- and workflow-oriented pragmatic interoperability. The next interoperability layer up from data interoperability consists of workflow engines orchestrating choreographies of workflow conversation among EHRs, and between EHRs and other health IT systems. Intelligent, transparent, flexible, workflow-managing process orchestration engines in the cloud will supply healthcare interoperability’s missing workflow layer.

Current healthcare interoperability rests on a two-legged stool. One leg is Syntactic Interoperability. One leg is Semantic Interoperability. (More on those below.) Plug-and-play syntactic and semantic interoperability is the holy grail of EHR interoperability. We hear less about the next level up: pragmatic interoperability (the linguistic science behind task and workflow interoperability).

Pragmatic Interoperability is the third leg missing from the healthcare interoperability stool. This five-part series describes pragmatics (a subfield within linguistics), its relevance to healthcare interoperability, and how to leverage process-aware workflow technologies, such as Business Process Management, to achieve task-workflow pragmatic interoperability. We need to add the crucial third leg of the healthcare interoperability stool.

Linguistics is made up of a number of subfields. You may think of them as a pipeline or series of layers from compression and rarefaction of sound waves to purposeful communication and coordinated action. The output from syntax is the input to semantics. The output from semantics is the input to pragmatics. In the pragmatics layer we do things with words to change the world to achieve goals. It’s actually way more complicated that how I make it seem. There are feedback loops. Linguists argue about where to draw the lines between syntax, semantics, and pragmatics. But this simplified model will serve the purpose of this series about pragmatic interoperability in healthcare.

Syntax and semantics are terms borrowed from linguistics, specifically, the study of signs. A sign is something, such as an ICD-10 code, that can be interpreted to have meaning, such as a medical diagnosis. Syntax is about relations among signs, for example relations among fields in an HL7 message or characters in an ICD-10 code. Syntactic interoperability deals with the structure of healthcare data (reminiscent of sentence diagrams in high school English class). It is necessary for transmitting healthcare data in a message from one system to another. Syntactic interoperability is the ability of one EHR (for example) to parse (in the high school English class sentence diagram sense) the structure of a clinical message received from another EHR or health IT system (if you are a programmer think: counting HL7’s “|”s and “^”s, AKA “pipes” and “hats”)

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Semantics is about the relation of signs to what they mean or denote in the world, such as a diagnosis, etiology, anatomic site, and so on. Semantic interoperability deals with the meaning of data. It is necessary for sharing meaning between transmitting and receiving systems. Semantic interoperability is the ability for that message to mean the same thing to the target EHR as it does to the source EHR or health IT system (think controlled vocabularies such as RxNorm, LOINC, and SNOMED).

Syntactic and semantic interoperability are not enough. They are just tactical tools. Pragmatics is about how we use syntax and semantics as a tool to accomplish goals. Semantics is about literal meaning. Pragmatics is about non-literal meaning. I will discuss pragmatics, in depth, in Part 4 of this series, but will introduce the idea of pragmatic interoperability below.

To review: Syntactic interoperability parses sent data structures; semantic interoperability preserves meaning across sending and receiving systems; pragmatic interoperability does something useful with the outputs of the former. It would not be grandiose to say a theory of healthcare pragmatic interoperability is a theory of healthcare interoperability, since syntax interoperability serves semantic interoperability, and semantic interoperability serves pragmatic interoperability.

Let’s start with a straightforward definition of pragmatic interoperability.

Pragmatic interoperability (PI) is the compatibility between the intended versus the actual effect of message exchange.” (Towards Pragmatic Interoperability in the New Enterprise — A Survey of Approaches)

Compatibility between intended effect versus actual effect of message exchange…

When you speak to me, you are trying to do something, to change the world in some way. Even if you do not explicitly tell me to do something, I grasp your intended meaning and likely help you do whatever you are trying to do. I consider the context of your utterance, your likely workflow (your goal, remaining tasks and their order, and which uncompleted tasks I might help you complete), and help if I can.

If you ask me if I know the time for the next scheduled surgery, I ignore your literal question (to which my overly literal answer would have been “Yes”), and respond to your intended meaning (”2:30″). I act in a pragmatic interoperable manner. The intended effect of you question is to find out the scheduled time (so that you can show up on time, so that you can complete your residency, so you can … and so on). The actual effect is you find out the time. Since intended and actual effects match, we achieve pragmatic interoperability.
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Key to modern conceptions of pragmatics is that human communication is not just encoding a message in my brain, sending it to you over a potentially noisy channel, and then you decoding that message. This is a naive model human communication. Among linguists an inferential model of communication replaced the simplistic encode/send/decode model of communication.

What do I mean by inferential? Speakers imply (suggest indirectly) and addressees infer (deduce from evidence and reasoning rather than from explicit statement). Consider an extreme example. Suppose everyday at 6PM an on-call physician sends a text message to a partner that everything is under control. Whenever no text message is sent, they both understand the partner needs to come in to help out. Since no overt message was sent, there is nothing to decode. Nonetheless, the address successfully infers the “speaker’s” intended meaning. This was an extreme example. For the rest of this series I will assume some overt token, a message, is exchanged. But the literal content of the message is insufficient to achieve pragmatic interoperability. Non-literal meaning must be inferred from shared background knowledge. The most important shared background knowledge to achieve healthcare interoperability is knowledge about tasks, workflows, plans, and goals, all of which are explicitly represented and automated by workflow technology.

Healthcare interoperability must incorporate more inference-based communication. The key technology to allow this to happen will be workflow technology. Workflow technology relies on explicit models of work and workflow. When these models (such as shared care plans) are shared, this is the context that make task and workflow interoperability possible. Shared context between sender and receiver make possible inferences necessary to achieve pragmatic interoperability. Current shared care plan-based health IT applications rely on humans to be the workflow engines, to react to changes in state and to trigger workflows. Increasingly this will be accomplished, or facilitated by software-based workflow engines.

A reasonable objection is that, designed right, all communication among health IT systems can be based on literal meaning (semantics) and not have to rely on non-literal meaning (pragmatics). I disagree. There is always some implicit message context that is not captured in the message itself. In some instances, perhaps it can be ignored. But in general, health IT needs to perform a better job taking into account the clinical context of sent and received messages. In this series, I will specifically focus on task, workflow, plan, and goal context, because we have an available tool to manage this context: workflow technology.

The earlier offered definition of pragmatic interoperability is deceptively simple, but nonetheless powerful. First of all, it makes intuitive sense. Clinicians can understand it, as in, do what I mean, not what I say, sort of way. Second, it can apply to relatively simple scenarios and to relatively complicated scenarios. “Effect” can refer to something as simple as sending someone (perhaps in another healthcare organization) a task to complete. Compatibility between intended and actual can be as simple as checking to make sure the task moves through its task life cycle (pending, started, resigned, started, escalated, complete and so on) to “complete” by a certain time or date. On the other hand, “effect” can refer to complex constellations of tasks, workflows, and mental states, as in, “I accept responsibility for completing all tasks in this assigned workflow, promise to complete them within one week, and inform you when they are complete.”

This series is about the science behind task and workflow interoperability, recently outlined in my recent 7000-word, five-part series Achieving Task and Workflow Interoperability In Healthcare. That series was about practical engineering. So if you are looking for a practical guidebook, go there. Here I am talking about theories supporting why I believe process-aware technology is key to achieving task and workflow interoperability.

Science is about understanding the world. Engineering is about solving problems. Scientific theories are abstract, tentative, and eschew practical consequences. Engineering is concrete, decisive, and about practical consequences. However, as Kurt Lewin, the famous organizational psychologist famously said: “There is nothing as practical as a good theory.” Have no fear, though; mine will be a gentle introduction to linguistics and pragmatics.

Stay tuned for (or proceed to… if there’s nothing there, it hasn’t been published yet) Task, Workflow, and Interoperability Definitions: Pragmatic Interoperability Part 2.

Read the Blog Posts on Pragmatic Interoperability by the Author
Here is an outline of this five-part series on workflow, linguistics, and healthcare interoperability.
  1. Task-Workflow Interoperability Benefits and Next Steps: Pragmatic Interoperability Part 5
Author


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Dr. Charles Webster
HIMSS14, HIMSS15, and HIMSS16 Social Media Ambassador! If you've got a healthcare workflow story, I want to tell it, blog it, tweet it, interview you, etc. Dr. Webster is a ceaseless evangelist for process-aware technologies in healthcare, including Workflow Management Systems, Business Process Management, and dynamic and adaptive case management.
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