Category Archives: Healthcare

Digital Psychiatry: will advancing technology support or destroy the patient-professional relationship?

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Last week I was invited to be on the panel for a lively debate on this thought-provoking question. I like such questions as they force us take a step back and look at the big picture gradually unfolding around us. Such questions make great topics for open ended debates, which the orgnaisers 1I have been attending this annual conference for a few years now and it has always been superbly organised. In fact it is betting even better with each passing year as its organisers (who are trainees themselves) are becoming bolder and ambitious in their vision. I want to congratulate the organisers of Mind, Body, Spirit: Psychiatry in Context 2014 Conference for a thoughtful agenda, smooth coordination and flawless execution. made sure it was (kudos!). Both the topic and the surrounding cricket memorabilia on display at Kia Oval, where it was hosted, enthused the audience and we fielded some very interesting questions and comments from them. In the end one hour was not enough to take every question on board, but I have noted the one’s that were asked and planning to pen down a few blog posts here to discuss those in detail. As it was the annual conference of London Specialty School of Psychiatry Annual Trainee Conference, there were hundreds of enthusiastic young psychiatrists in the audience. It was interesting to note that while the senior psychiatrists 2Many thanks to Dr Michael Maier in front row, who alerted me just in time about the precarious position my chair found itself in (with one leg halfway off the stage) while I was delivering my opening statement. That fall would have made a more spectacular sight to tweet than the routine image I have included above. in attendance focused on perceived usefulness of modern technology, the younger generation asked questions pertaining to the management of available technology. I have talked about such a split between pre-adoption and post-adoption generations in past, but it was interesting to see it playing out in reality in such a large crowd. My fellow panel members, who were Richard Graham (Consultant Psychiatrist, Technology Addiction), Alex Langford 3Alex has shared his thoughts on the issue before the debate on his popular blog. (Blogger), André Tomlin (The Mental Elf) and Mark Brown (One in Four) freely shared their insights and nuggets from their own experience. The fun of having open ended debates is mostly in the ability to accommodate a rich diversity of viewpoints, which was clearly evident in the opening statements of each of the panel member. Everyone had a different angle on the question, but the message remained the same – we should try and understand the process of technological change in order to use it to be even better clinician tomorrow.

I think that it would be useful to save my opening statement for this debate here for an “internet peer-review” and may be for the sake of posterity. Maybe I can revisit this page after a few years to compare notes with the reality of tomorrow.

Here is complete text of my opening statement at Mind, Body, Spirit: Psychiatry in Context. 26th November 2014:

I am a medical psychotherapist by training. One thing I have learned well is that relationships are not set in stone. Although bound by some basic rules, all relationships evolve to become something better or worse. They are always in a constant state of flux. People change and so do their relationships. Time changes, so do the relationships that exist in that time period. Society changes and so do the relationships living in that society. Doctor-patient relationship is not an exception. It is changing and evolving as we speak. We don’t know yet whether it is for good or bad.

Technology has brought information on our finger tips. A therapist can no longer be a blank slate to the patient as he has been trained to be. Thanks to social networking, patients now know who you are, what your interests are and what is your friend circle like. Is this a good thing or a bad thing? Would it limit my choices of the model of therapy that I can use? I don’t know. What I do know is that the rules are different now, and I have to get a better sense of it before I can do what I want to do, that is to help a patient become better. Even if it means rewriting the rules of my practice, which were framed in a different time and generation, I should be open to it. It should not mean that I exclude myself from the benefits of technology and the connectedness it brings. Avoidance is not an option – that’s what we tell our patients in cognitive behavioral therapy. I believe that we should adopt this change and adapt. I believe that by harnessing this shift we can be better doctors and create more meaningful relationships with even greater number of patients. It might sound a bit like the proverbial dream of a manager in NHS, but it certainly is achievable.

First shift should be a shift in our perceptions of what doctor-patient relationship is. In actual terms terms it is a partnership to solve a problem. To efficiently solve the problem both parties have to collaborate and exchange information. However unlike historical archetypes, doctor is no longer the primary information provider to patients. The barriers to access information have fallen so low in last two decades that anyone with an internet connection can get more information about their symptoms than the doctor they are planning to see. We are no longer the expert, internet has reduced us to a generalist who knows a fair bit about everything. The balance of information power has tilted in favour of the patients. In turn our relationship with them has inverted, at least in certain dimensions of knowledge. Gradually this would change how we are perceived by public. In future we, as doctors, might be valued more for our skills and experience than for our knowledge. Not a popular thing to say to an audience which is full of trainees who are just starting on a journey of a lifetime of experience, but it looks likely to happen in near future. IBM, the oldest information technology corporation, has developed a software solution aptly named as Watson after the famous Dr Watson in the novels of Sir Arthur Conan Doyle. This new age Watson is “training” to be a doctor, hold your breath, a specialist doctor in all known disciplines of modern medicine. It would be able to learn more than we ever can. It would be able to update its knowledge in real time, a feat impossible for anyone of us in this day and age of information explosion.

I took time to say yes to the invitation for today’s debate. I needed time to think whether I have something meaningful to say on the topic. The more I thought, the more I realised that it is a question with multiple layers. At its heart it is asking are today’s doctors disposable in future. Is our profession, one of the oldest professions in history, actually just a temporary solution to a necessity we have as a society. Would technology replace us eventually? I don’t know what would happen after 100 years, but in our lifetime the answer would be no. On the contrary we are sitting on the cusp of a information revolution 4I did notice some raised eyebrows in audience at this point and wondered if some people still underestimate the changes happening around us. in doctor-patient relationship. If we design the right tools, if we understand the changes, if we consider patient to be an expert in their problem and ourselves as an expert in delivering the solution, if we allow doctor-patient relationship to evolve with the demands of time, then yes we have the biggest opportunity right in front of us.

footnotes

footnotes
↑1 I have been attending this annual conference for a few years now and it has always been superbly organised. In fact it is betting even better with each passing year as its organisers (who are trainees themselves) are becoming bolder and ambitious in their vision. I want to congratulate the organisers of Mind, Body, Spirit: Psychiatry in Context 2014 Conference for a thoughtful agenda, smooth coordination and flawless execution.
↑2 Many thanks to Dr Michael Maier in front row, who alerted me just in time about the precarious position my chair found itself in (with one leg halfway off the stage) while I was delivering my opening statement. That fall would have made a more spectacular sight to tweet than the routine image I have included above.
↑3 Alex has shared his thoughts on the issue before the debate on his popular blog.
↑4 I did notice some raised eyebrows in audience at this point and wondered if some people still underestimate the changes happening around us.

Model Driven Development (MDD) in future-proofing Healthcare IT Solutions?

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Big organisations in information driven industries are gradually moving away from creating software data tools themselves. The task of creating software is getting outsourced to anyone with an interest in it by using an approach referred to as Model Driven Development (MDD). Considered a fanciful idea just a few years ago, MDD has moved from a novel concept to a pragmatic business necessity in large corporations. App store by Apple for iPhones is just one of the examples of the success of this approach. Implementing MDD in healthcare can prevent the sector from spending billions on complex IT projects, while delivering comparable or even better software tools.

The main benefits of such an approach in healthcare could be:

  1. Reduction in development cost and time
  2. Interoperability between different software
  3. Localised specifications to better address complex variable needs
  4. Better opportunities for clinicians and patients to engage in software development

MDD approach requires the healthcare authorities to look at the healthcare IT as an ecosystem rather than as a project. It hence takes on the responsibility for establishing standards and benchmarking, providing an immense room for policy innovations. MDD software approaches have proven to be inherently adaptable to changing circumstances. This makes these approaches an excellent fit in healthcare settings wherein changes in government, technology or medical knowledge require resilient IT solutions (“future proofing”).

Healthcare IT can benefit by learning from other information driven industries. However in most cases, the project leadership is unable to see the big picture in both IT and health industry. This is because in healthcare, creator of technological and data solutions is not usually the consumer of these tools. To succeed and stay ahead of the curve, healthcare IT would need to foster leadership positions for people uniquely qualified to take on integrative leadership roles, which can facilitate such vision. In the UK, some healthcare authorities have started recruiting Chief Clinical Information Officers (CCIO) to their boards, which is an encouraging step towards this direction. Otherwise we would be perpetuating this strange dichotomy wherein patients and clinicians are technophiles at home with smartphones, but technophobes once inside healthcare settings. 1The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

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↑1 The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

How healthcare industry is uniquely placed to gain from Big Data revolution

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Medical information doubles almost every few years and the rate of production of new medical information is accelerating. Advances in medical knowledge often make established treatment models obsolete. In a typical year, frontline clinical staff would have 22000 new peer-reviewed articles, 30 new drugs and 6000 new combinations of drug compatibilities to consider in addition to their existing knowledge of medicine. The number of drugs has grown 500% in just the last decade and the technological advances in medical imaging are producing more data than ever before for the same procedures (e.g. High Resolution CT Scans). Not only medical data has exploded in recent years, it has also become more accessible to both the patients and providers alike.

Traditionally, meaningful information has been extracted from large sets of data by sampling a representative portion of the data set. Sampling methods, with all their limitations, were essential as we did not have the tools and resources to comprehend the entire datasets. However with newer technology this limitation is rapidly being removed. One such approach, encompassing various techniques commonly referred to as Big Data, is helping information driven industries to analyse entire datasets regardless of their size and scope. At the heart of these new techniques is a simple premise – ‘why analyse a fraction of data when we can analyse everything’. Big data also helps us to move away from the post-hoc statistical analyses which are unable to provide real time measurements. Although other information driven industries have been quicker to adopt big data models, healthcare industry is uniquely placed to benefit the most from it for the following reasons:

  1. Most healthcare data is recorded and validated.
  2. It spends billions in research and development.
  3. Healthcare data is ever increasing, thereby stretching the resources.
  4. It would help to focus on preventative measures.

Big data models have emerged only in last few years and their growth has been fuelled by internet based companies like Google, Yahoo! and Facebook who face the challenge to meaningfully analyse the datasets generated by billions of individuals.

‘Flu trends’ by Google is just one example wherein the algorithmic analysis of big data sets (i.e. all search queries) is providing almost real-time estimates of current flu activity throughout the world. This online tool, which has been designed by engineers at Google with little background in healthcare, is accurate enough to closely match the official government estimates of flu activity and still has the advantage of spotting the emerging trends 2-4 weeks before healthcare agencies.

This is just one example of the transformative power of big data in healthcare.1The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

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footnotes
↑1 The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

Evolving Dynamics of Information Flow Between Clinicians and Patients

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One of the core drivers in healthcare industry is the information about health and disease. Clinicians are performing the task of eliciting information about illness from the patients, filtering out the noise from signals and producing actionable information, which leads to interventions. They are also burdened with the task of storing (documenting) and disseminating this information to patients and other relevant healthcare professionals. Some estimates put the time spent by a clinician in eliciting, documenting, storing and disseminating this information as up to 2/3 of their clinical time, with less than 20% actually spent in performing interventions (treatment). The role of information is so central in healthcare that it can be argued that its main business is the business of information. Therefore any factors which can alter the dynamics of information in our society are bound to affect healthcare business. Last two decades have witnessed many fundamental shifts in these dynamics.

If we look beyond the obvious proliferation of technology in the form of round the clock access to information from the internet from mobile computing devices or via online social networking, we would find that the way we consume information is undergoing a fundamental change. As a society, we are rapidly moving away from synchronous interpersonal communication (wherein both the originator and recipient of information have to be in same place at same time) as being our dominant form of communication. This shift towards asynchronous communication is not new, as it has been a part of human civilisation ever since we learned to draw in caves in ancient times. Asynchronous mode of communication became significant after the invention of paper and printing, but internet is giving it the impetus to become the dominant form of communication in human society. This also means that an ever larger amount of information is accessible by ever greater number of individuals.

Fig 1. Medical information triangle: Dominance of the asynchronous flow of information

Fig 1. Medical information triangle: Dominance of the asynchronous flow of information

In healthcare settings it means that the clinician no longer might be the primary information provider to a patient. Today both doctor and the patient have become voracious information consumers, using easily accessible knowledge to inform our decisions in millions of different ways. This shift is gradually changing the public perceptions of healthcare professionals, who are now less valued for their knowledge but more for their skills and experience. With easy access to detailed information, a tech-literate patient could possess more information about his illness than the doctor who had to study several thousand illnesses. However despite that our healthcare IT systems are usually designed to suit 20th century practices i.e. one to one synchronous interactions between the doctors and patients. This approach fails to capitalise on possible advantages offered by the asynchronous communication which has the potential to dramatically increase the reach of individual clinicians. But most importantly it fails to correct one of the most important drawback of the dominance of asynchronous communication, i.e. it is more error prone than the synchronous modes of communications. This is because unlike synchronous means of communications, which has spontaneous feedback loops (doubts can be immediately clarified by interacting parties in real time), feedback loops have to be created in asynchronous information ecosystems.

As an industry we have made little progress in this area, and still treat to keep most of the patient information as the proprietary information of the organisations. By evolving future healthcare systems in the direction of the shift in the flow of health information, the industry can potentially boost the productivity of individual clinicians. Rather than limited by traditional physical case load limits of a few hundred patients, a future clinician can practice on an unprecedented scale when aided by the right technology and policies.1The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

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↑1 The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

The Problem of Disconnected Data in Healthcare

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Healthcare data is mainly collected and stored in the following three separate data pools:

  1. Clinical data
  2. Financial data
  3. Research data

Because the responsibility for collecting, storing and utilising this data rests with different individuals or institutions (clinical – hospitals, clinics; financial – managers, governments; research – universities, pharmaceutical companies), they remain largely isolated from each other with little interconnectivity. The disparate systems on which these datasets are located are typically unsuitable for complex integrative analysis. This disconnect between healthcare data can be detrimental to the early identification of important healthcare trends or adverse events, as highlighted by the withdrawal of a popular pain relief drug rofecoxib in 2004.

Rofecoxib was approved by US Food and Drug Administration in 1999 and gained widespread acceptance amongst physicians worldwide who prescribed it to over 80 million people worldwide. In 2004, a California-based integrated managed-care consortium Kaiser Permanente connected clinical and financial data to compare the risk of adverse cardiovascular events for users of rofecoxib against a similar drug; it found that rofecoxib might have been responsible for more than 27,000 avoidable myocardial infarction (heart attack) and sudden cardiac deaths between 1999 and 2003. This study led to a voluntary withdrawal of the drug from the market. Interestingly between 1999 and 2004, similar conclusions were suggested by a number of small scale studies, however none was considered large enough to raise sufficient concerns. The simple act of combining clinical and financial data provided the crucial research dataset that was required to trigger one of the largest medication withdrawals in history.

Although the above example is a powerful indicator of the potential benefits of having an integrated approach on healthcare data, large scale implementation of such approaches have proven to be challenging and therefore they has remained underutilised. In the UK, implementation of Payments by Results (PbR) in National Health Service to integrate clinical outcomes with financial remuneration has produced mixed results. Such approaches usually require a fundamental reorganisation of the industry processes and support by technology appropriate innovations in policy.

One such example is the recently launched government funded Secure Unified Research Environment (SURE) project in Australia, which aims to overcome such limitations by providing a central datacenter where researchers can form connections between data sources and access the necessary computing power required to perform such analysis. In its short span of active operation, researchers using this integrated database have been able to confirm the intuitive beliefs that the older Australians are more likely to have higher consistency of care, and that lower consistency of care is associated with geographical remoteness. It also led to a counter-intuitive discovery that wealthier and more highly educated Australians have a lower consistency of care.

It is important to note that although researchers were able to test intuitive beliefs using more complex and time consuming methods before the existence of SURE database, counter-intuitive discoveries would not have been possible by looking at a single dataset alone.1The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

footnotes

footnotes
↑1 The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

Why healthcare sector is struggling with its digital reincarnation?

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In the future, when we would look back at this time, healthcare informatics would be seen as the biggest healthcare revolution of our generation. Inside the wider field of healthcare informatics, mental health is arguably one of the most information rich fields. Most mental health problems are chronic in nature, necessitating several encounters between the clinician and the patient over many years. In addition, mental illnesses are poorly understood in terms of their exact neurobiological mechanisms, which make it difficult to have standard laboratory tests to quickly establish the diagnosis. In practical terms, this means that unlike other professionals in healthcare a mental health professional does not have the luxury of quick and reliable methods to make clinical decisions. Therefore the practice of mental health is marked by multiple lengthy clinical interactions with individual patients and the information generated by such encounters differs both in quantity and quality from most other fields of medicine.

The information rich practice of a health professional makes it vital that they are actively engaged to shape the agenda in the wider field of health informatics. In this article I am trying to cover some of the current issues with health data and informatics. It is based on the insights I gained from being at a unique vantage point of a psychiatrist and a tech entrepreneur, but the problems and potential solutions I am highlighting are equally applicable to every part of the modern healthcare IT systems.

When we think of using information technology in healthcare settings, we are mostly focussing on its transformative potential. The broad assumptions about the immense benefits that IT can bring to this sector are undoubtedly valid, but successful implementations of such technologies have proven to be difficult and challenging. Despite being an early adopter of information technology, healthcare sector in the developed world is still underutilising this technology to the peril of the patients and policy makers alike. While other major industries are moving on to the next stages of their digital transformations, healthcare sector is still negotiating with the transition from paper based records to digital records. Many factors unique to healthcare make this transition difficult but a commonly seen theme is the slow pace of policy innovation in healthcare IT.

In this blog I would try and cover many challenges, and potential solutions to these very problems in healthcare IT.1The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.

footnotes

footnotes
↑1 The content of this post was later included in a chapter in the following publication: Tyagi, H. (2013). Health data technologies: the current challenges. In NEXUS STRATEGIC PARTNERSHIPS (Ed.), Commonwealth Health Partnerships. London: Nexus Strategic Partnerships for the Commonwealth Secretariat.