Patient non-compliance to treatment regimens has always been a significant challenge in chronic disease care.  To quote an excerpt from a rather interesting MedScape CME education article, “Any drug that you do not take does not work” [1]. Patients' day-to-day decisions have a tremendous impact on the reported efficacy of treatment regimens and more importantly on their own health. Therefore, in the information age the favorable advocacy is for patients to be converted into active, informed participants taking ‘charge’ of their individual care management processes in order to guarantee the overarching success of the healthcare delivery system as a whole. Physicians must help patients take charge of their conditions by encouraging them to set self-management goals but also allow them to become actively involved with the diagnosis and selection of treatment options for their ailments.

                The old models of care where physicians would tell patients what to do and try to motivate them to change their habits or ways does not have a place in today’s day and age for a plethora of reasons which eventually boil down to fact that the average internet-enabled individual today does not like being told what to do without forming his / her own opinions.  Working out a fool-proof way of getting through to the modern patient is one with substantial medical and economic ramifications.  To shed some light on the substantial cost implications of effectively taking control of patient behavior, it is interesting to note that a majority of healthcare spending (outside of public-health expenditure) is affected by consumer choices.  In fact, 69% of healthcare spending – including spending for catastrophic events attributed to chronic conditions, discretionary care and end-of-life care – is largely subject to individuals’ choices and behavior [2].

                Assimilating the facts, therefore, informing patient behavior clearly has ramifications on both the effectiveness of patient care as well as healthcare economics. Now let us go over some interesting approaches which are gathering momentum in regard to informing patients about the state of their health and therefore indirectly allowing the healthcare system to begin gaining control of ‘patient behavior’.  One way to make patients active participants in healthcare administration is to allow them to actively partake in the diagnosis of their health and further actually ‘operate’ diagnostic devices without scheduling appointments. This very concept is being pursued by a startup company from Ohio – HealthSpot [3], as well as Mayo Clinic [4] in the form of ‘diagnostic kiosks’ and is expected to make a revolutionary impact in regard to patient empowerment and reducing healthcare costs. Such technology has potential for impacting diagnosis and administration of treatments for minor and common health conditions such as the cold, earaches, sore throat, sinus infections, upper respiratory infections, rashes and skin conditions and eye conditions but tend to be less suited to management of ailments of less able-bodied patients with chronic conditions.

                Beyond the kiosk concept, several medical device startups – some with FDA 510k cleared product offerings – [5] as well as major technology firms such as Apple and Samsung are investing heavily in technology that can monitor a user's health using their mobile devices.  As per a recent BBC News reported survey [6], more and more patients today are going to their general practitioner with preconceived notions regarding their expected treatment pathways which they glean based on information from apps and the internet. However, the BBC article also reports that often a patient's online diagnosis is not useful to the physicians. 

                From the standpoint of the Devil’s Advocate to the above concepts, the hypothetical scenario of generating a population of non-medical trained but highly opinionated patient could be quite worrisome… In such a scenario, what might begin as a social issue of inappropriate self-administration of inordinate doses of over-the-counter medication may in the long term create a faction of quasi-trained healthcare professionals – or worse still, medical software / apps – with a greater power over patient beliefs than physicians themselves!  So, how far must be actually go with regard the liberties offered to the active and informed patients in the care management process..?

References:
[1] “Adherence: The Silent CV Risk Factor” on Medscape. http://www.medscape.org/viewarticle/582903
[2] McKinsey International Survey on Healthcare’s Digital Future: http://www.mckinsey.com/insights/health_systems_and_services/healthcares_digital_future
[3] HealthSpot: http://www.healthspot.net/
[4] Mayo Clinic Telehealth Kiosks: http://medcitynews.com/2014/10/mayo-clinic-telehealth-kiosks/
[5] http://medcitynews.com/2013/01/iphone-app-for-retinal-images-cleared-by-fda-could-expand-telemedicine-eye-exams-video/
[6] http://www.bbc.co.uk/news/technology-29458143

This post extends upon my previous blog entry on the 'waves' of healthcare IT adoption. The focus this time is on assimilating primary and secondary research in regard to ascertaining the optimal direction for new healthcare IT innovation and entrepreneurship initiatives, given the current healthcare climate...  

Healthcare IT adoption has been arguably most impactful in terms of enabling patient involvement in care management and accessibility to their digital health data through web-based or mobile applications. To successfully ride these trends of the third wave of healthcare IT adoption, healthcare companies need to follow the proven models of champions from the digital-service era like Google and Facebook by starting with a single focused end-user offering and then gradually add ergonomically designed conveniences which both keep the patient’s interests in mind and hold their attention, without introducing overt complexity. True empowerment in the digital era is about building value while ensuring comfortable interaction in a manner that necessitates negligible training (or none at all) to get acclimated to a new digital offering for patient enablement.

                In my last blog post we drew insights regarding what patients really want from digital healthcare through primary research [1].  But digital health systems around the world face challenges as well which is why any new patient enablement service offering needs to be positioned at the trade off of technical limitations on serviceability and scalability, and of-course patient needs. Limitations at the system level stem from the growing burden of chronic conditions which in-turn is a function of an aging population – 18% of the US population will be over 65 years old by 2025 – and the explosion of ‘lifestyle diseases’ relating to stress, mental illness etc.. But recall that over 70% of patients over 50 years old want digital healthcare services nearly as much as their younger counterparts for services such as finding and scheduling physician appointments [2] – therein stems the problem of scalability.  While health promotion and prevention services are easy to advertise in a viral fashion through the digital media, managing prospective clientele and the resulting data from client-servicing has proven to be the technical bottleneck given that what patients really want in regard to better understanding the state of their health – as per primary research [1] – is fast availability of a personal contact person. 

                Mushrooming hospital activity, unrelenting technological change, and costs of care rising at a rates faster than the general economy have reflected in increased financial wherewithal for the healthcare industry addition, while there remain concerns that the healthcare system is failing to meet the expectations that many people [3]. Common problems encountered by patients and ones that remain to be addressed by the healthcare IT revolution for patient enablement include reducing avoidable admissions and relieving the frustration that arises from long wait-times and having to repeat information and undergo repeat testing from a confusing array of healthcare professionals.  
                The E-care digital revolution attempts to address these needs through the delivery of customer service via Internet-based user accounts, social networks and mobile applications, rather than call centers or service counters. E-care can significantly lower the cost of customer service operations [3] and despite their most obvious setback viz. the complete unavailability of a personal contact person, such digital services are in increasing demand by young, digitally enabled customers for whom online research and review of products is unremarkable.

                Assimilating the facts, especially given that the healthcare system is particularly failing in regard to servicing the needs of the elderly and those with chronic conditions while the use of mobile healthcare applications is strongest primarily among younger people, enabling services addressing the looming issues of healthcare accessibility via online platforms which include as much connectivity to ‘real people’ as possible seems to be the right direction for new healthcare IT innovation and entrepreneurship…


References:
[1] McKinsey International Survey on Healthcare’s Digital Future: http://www.mckinsey.com/insights/health_systems_and_services/healthcares_digital_future 
[2] Practo – the doctor search engine. www.practo.com 
[3] Why companies should care about e-care: http://www.mckinsey.com/insights/marketing_sales/why_companies_should_care_about_ecare?cid=DigitalEdge-eml-alt-mip-mck-oth-1408 

In earlier blog entries we have discussed specific avatars of Information Technology (IT) in the healthcare industry and touched upon how IT has been a driver of several megatrends. An interesting McKinsey publication from July 2014 [1] summarizing insights from a recent international survey highlights several key aspects of the healthcare industry wherein IT adoption has made a positive impact. The effect of IT has been reported to have occurred in a cascade of ‘waves’, occurring in chronological order, impacting:

1. Automation of standardized and repetitive tasks (eg: accounting and payroll).
   
2. Advocacy for the promotion and rapid adoption of health-IT through effective policy changes (eg: the Health Information Technology for Economic and Clinical Health Act in the United States, amongst other policies worldwide) which were made seemingly keeping in mind the goal of assuaging the world’s privacy concerns by advocating a system riddled with a myriad of regulations.
   
3. Full digitization of the healthcare enterprise, including but not limited to electronic health records and digitization of medical imaging for radiology practices – the subject of my earlier blog entries relating to RIS and PACS – which has holistically brought patient-care and patient-needs to the forefront of the care delivery mission.  

This third IT wave has been arguably the most impactful in terms of patient-enablement for accessibility to their digital health data through websites, social media and smart phone applications.  But have the agencies behind this third wave (which have incidentally been primarily ‘non-healthcare organizations’) been effective in understanding what patients really want from digital healthcare..?

In retrospect, granted our world is being revolutionized by technology driving healthcare digitization and advocating securely accessible data, how well have healthcare organizations been reading the signs in regard to patient-needs en-route to the goal of digital patient-enablement..? The McKinsey Digital Patient Survey conducted in 2014, in Germany, Singapore, and the United Kingdom, with a sample size greater than 1,000, reveals some surprising insights…

1.  75% of people ‘want to use’ digital services for healthcare!  Healthcare policy decision makers often cite data that point to relatively low usage of digital healthcare services and blame this on patient sensitivity to data privacy.  Survey results indicate quite the contrary; in fact, patients don’t need to be convinced about privacy issues but instead care about the quality of the digital services and demand that existing services meet their ‘needs’.
2. Over 70% of older patients (i.e. over 50 years old) want digital healthcare services nearly as much as their younger counterparts! The difference between the two groups lies in the fact that younger patients are more keen on health promotion and prevention services, the older population seeks information about services for acute and chronic conditions.
   
3. The demand for ‘mobile’ healthcare is not universal!  While the demand for mobile healthcare applications is strongest primarily amoung younger people, both young and old patients care for fast availability of a personal contact person and the ability to access services via an online platform. So, at the global level, given that 60% of a lifetime’s healthcare costs occur after the age of 65, the fact that the human population is aging rapidly and more people are living longer with average annual  growth rates of persons aged 80 years or over being approximately twice as high as the growth rate of the population over 60 years of age (recall that by 2025 over 18% of the US population will be over 65 years old!) [2], are mobile apps really critical to the future of healthcare digitization..?  Perhaps not… Here is an interesting article to supplement this thought: http://vincedasta.com/p/save-your-money-dont-build-an-app/
   
4. Focused digital services that work ‘fast’ are preferred over dinosaurs that offer comprehensive platforms which encompass a wide spectrum of customer services that are often too complex to navigate and conduct routine tasks.  Amongst routine tasks, “finding and scheduling physician appointments” and “repetitive administrative tasks” (eg: prescription refills) have been identified as services with which most people require assistance.
   

Riding the trends for the third wave of healthcare IT adoption, healthcare companies should follow the models of champions of the digital-service era like Google [3] and Facebook – start ‘small’ with a focused end-user offering and then continually add new services which both keep the customer’s (i.e. the patient) attention and build value, while ensuring the customer is comfortable interacting with the digital offering and requires little to no ‘patient enablement’ assistance to get acquainted with a new service.

References:
[1] McKinsey International Survey on Healthcare’s Digital Future:     
     http://www.mckinsey.com/insights/health_systems_and_services/healthcares_digital_future 
[2] http://www.un.org/esa/population/publications/worldageing19502050/pdf/90chapteriv.pdf
[3]  Jeff Jarvis. What Would Google Do?, first edition, New York, NY: HarperCollins, 2009.

Radiology information systems with picture archiving and communication capabilities have together provided modern radiology practices with the unlimited data storage and sharing capabilities necessary to cope with the ever-increasing routine data-demands.  These systems offer patient-specific medical image management in a digitized format, according to the well-known standards elaborated in Digital Imaging and Communications in Medicine (DICOM) [1]. Digital image storage has potential to enable data access in a unified manner by departments even outside of the radiology department of a hospital provided server-side components and storage facilities are shared by all departments in the hospital.  At the viewer’s end, digital systems can further be optimized for access by viewer computer systems (i.e. client systems) according to custom requirements of each clinical department in terms of resolution of rendering and image-processing capabilities.

Image digitization has paved the way to effective structural visualization of diseased tissue or organs;  today imaging has begun to have implications that transcend merely diagnostic value and is entering the realm of surgical planning minimally- or non-invasive examination and treatment through the realistic depiction of three-dimensional ‘depths’ of medical imaging as it relates to specific anatomical shapes. Image post-processing capabilities embedded in digital image management systems today often amplify the value of visualization by facilitating extraction of two or three dimensional measurements which is useful for purposes of reporting, and may employ cutting-edge digital signal processing technologies that quantify (or semi-quantify) either static or time-series image datasets. This augments the end-user’s cognitive capabilities by serving as a physician’s second-reader to accurately diagnose disease or plan out surgical decisions. 

Quantification of images has in-turn led into the concept of computer aided diagnostics (CAD), wherein a physician receives a diagnosis or ‘result’ from a non-human entity.  CAD may be dubbed as ‘clinical intelligence’ to support daily radiology tasks and is often based on techniques employing machine-learning and data-based rule-learning technology which actually ‘arrive at’ a clinical decision rather than merely ‘guiding’ a physician towards one.  This concept itself germinated in the 1960s but today has matured into a major focus of biomedical and clinical research relating to imaging-based biomarker discovery. Developments in this field of CAD have been incorporated into the routine diagnostic radiology approach to the structural screening of breast cancer on mammograms, early detection of heart disease [3-5] and even estimation of rupture risk of vascular aneurysms, to name just a few applications being investigated in this mushrooming space. But wait… there’s more!  We can do even more with imaging today…

One of the research domains receiving the most attention from funding agencies including the National Institutes of Health in the recent past has been the enabling of existing capital equipment with capabilities of imaging neuronal, cardiovascular and cellular ‘function’ as an extension to the convention of visualizing the structure of tissue or an organ.  As opposed to structural imaging, functional imaging focuses on revealing physiological activities within a certain tissue or organ by employing medical image modalities that usually reflect a spatial distribution of injected tracers or probes within the body.  Functional imaging has probably seen some of its greatest application in cognitive neuroimaging i.e. understanding the link between neuronal activity and functional imaging signals.  A few functional imaging modalities which have made an impact in this space, to name a few, include positron emission tomography (PET), infrared imaging, Electroencephalography (EEG), Magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) [2] to detect blood-oxygen-level-dependent contrast material as an indicator of brain neuronal activity, and diffusion weighted imaging conducted by the Human Connectome Project which aims to understand the details of neural connectivity and build for the first time an integrated roadmap of structural as well as functional neural connections within the brain [3]…


References:
[1] DICOM. http://medical.nema.org/Dicom/    
[2] Journal of Neuroscience Methods 74 (1997) 229–243. http://neurosci.info/courses/systems/FMRI/kim_fmri.pdf
[3] http://www.humanconnectomeproject.org/about/

Megatrends are defined as global, sustained and macroeconomic forces of development that impact business, economy, society, cultures and personal lives, thereby defining our future world and its increasing pace of change.  Three megatrends most relevant to medical imaging and radiology have been: a) Information Technology (IT) and Big Data; b) Demographic shifts defined by an ageing and growing population affecting healthcare expenditures; and c) Electronic, remote and mobile delivery of goods and services.

Our first megatrend is a global trend seen across all industries and one that has affected each of our personal lives over the last 5 years –the need to collect large amounts of data.  Be it photographs, documents, medical images or cloud services on our iPhones which justify never deleting another photograph to make space on our devices, the ‘big data’ megatrend has touched each of our lives.  IT and the effective use of the same is an important cornerstone of the megatrends observable in the healthcare space today. Efficient management of vast amounts of rapidly generated data as well as management of clinical workflows is largely dependent on the development, accessibility and scalability of IT infrastructures supporting the healthcare industry.

Our second megatrend relates to healthcare spending.  60% of a lifetime’s healthcare costs occur after the age of 65 years and by 2025 over 18% of the US population will be over 65 years old – an increase from 13% in 2010, amounting to an additional $4.5 trillion in healthcare spending!  With an increased number of people spending time and money in hospitals, there is also a simultaneous growth in the number of deaths owing to medical errors – a whopping ~100,000 per year.  Therefore, technologies for healthcare which present opportunities to save costs in terms of patient management while delivering optimal medical care with increased success rates and reduced rates of error are the ones which will define the healthcare delivery models of future.  Such technologies will cumulatively shape tomorrow’s cost of another year of healthy life…

The third megatrend of great relevance to healthcare is electronic delivery of goods and services in an era of rampant wireless device proliferation.  Remote monitoring of patients and disruptive non-invasive diagnostic technologies are now ubiquitous while digital workflows such as teleradiology and distributed care which reduce costs and improve home healthcare efficiency as they allowing caregivers to manage time and resources more effectively.  The ‘extended hospital’ today includes disruptive radiofrequency wireless-enabled technologies for remote diagnosis of cardiac health or injury and even telemonitoring technologies for monitoring patients over a wireless network, web video or the traditional telephones to reduce risk of death amongst critically ill or old patients while improving compliance in regard to medication regimens.

Finally, to conclude on these megatrends and their affect on the healthcare practice, it is important to note that although technology revolution defined by these megatrends is ubiquitous, change is SLOW. Development and deployment of advanced IT-enabled goods and services in healthcare hasn’t enabled the same levels of transformation that have occurred in other industries for a number of reasons, the most important being the fact that healthcare is a brutally regulated space which is monopolized by a few omnipresent heavy-weights with the capital to surmount these regulatory hurdles. However, despite these shortcomings of technology adoption in healthcare and the unfairness of the competitive landscape, ‘healthcare IT’ is an umbrella for a host of technologies which together constitute the forefront of an overwhelming confluence of interests from stakeholders that range from the lay patient to physicians and business leaders.  The digital, electronic and mobile technologies discussed in this post as well as several others breaking the threshold between academia and industry every day, will make a far-reaching financial impact that will disrupt the industry and drive real change in patient care, data management and healthcare-related business process workflows.

References:

* Images from http://suemontgomery.org/big-data-in-healthcare-collaboration-and-interoperability-are-essential-to-its-success/ , http://www.itpro.co.uk/strategy/20647/two-thirds-firms-will-invest-big-data-year-claims-gartner , http://blog.agfahealthcare.com/2013/06/11/the-icis-world-cloud/