Restart the Digital Health Revolution by Making Healthcare Delivery Easy
This chat we had with Martin from Think Research touched on the broader concept of Analytics for Good. As luck would have it, on July 19, 2019 for the ABD 2019 Conference we’ll be bringing in experts from across the healthcare and analytics industry to explore this topic even further. Get your tickets today!
by Kitty Chio
The digital health revolution was inspired by increased connectivity from wearables, which are now virtually inseparable from us, and the rise of a spectrum of virtual care services from eConsultations, eReferrals to remote monitoring; not to mention, the invention of precision medicine and data-driven treatment which allowed us to reimagine the entire patient experience and treatment journey. Though, as much as we would like to think that Ontario is the perfect launchpad in Canada to start this revolution, digital health has not taken off as rapidly as we thought.
For one, the “iterate fast and release often” philosophy does not apply in health tech given the higher than normal barrier in regulatory oversight. The research-practice gap is also notoriously wide in the healthcare industry which hasn’t changed as drastically as expected despite recent Digital and AI disruptions. Patient privacy, regulatory adherence, and the lack of strong technology infrastructure are roadblocks that continue to plague the industry. Martin Persaud, Associate Vice President of Business Development at Think Research in Toronto, shares some of these sentiments but also believes the sluggish adoption of digital health in Ontario might be due to more deep rooted issues.
Starting late in the game
Digitization undoubtedly eliminated operational inefficiencies by introducing the ability to organize, store and share Electronic Medical Records (EMR). However, ever since the dawn of EMR in the 1990s, physicians in Canada were not inclined to digital adoption due to the upfront financial investment and disruption to the existing clinical workflow. To compensate for the late adoption, healthcare providers and organizations accelerated their migration to EMR with separately developed IT systems, which eventually gave rise to data silos and incompatible data sharing. Despite hefty efforts in EMR integration that quickly followed in the 2000s, only 58% of clinicians could access interoperable patient data by 2016.
Martin claimed that, even today, aggregated data is hard to obtain for health tech companies, making it difficult to maintain a single patient record and effectively track patient outcomes while improving clinician workflows. He attributed the barrier in open data sharing to continued issues in EMR interoperability, growing privacy requirements (PIPEDA, HIPAA), and more fundamentally, the inability to fully digitize patient information without burdening clinicians with administrative overhead. Martin learned that many physicians do not feel well served by the new wave of technology and believe their time is better spent on actual patient interaction instead of data entry in front of a computer. Without clinician buy-in, there is no data feedback loop to or from analytics systems, and ultimately, any insights on patient outcomes or treatment effectiveness are forever lost.
Learning from the EMR fiasco in the past, policymakers are now learning to balance between overall cost reduction, upfront investment in technological progress, and quality patient care. This is not an easy undertaking—how can we invest in making virtual services ubiquitous in Canada and transform this archaic one-size-fits-all healthcare system to one that’s more personalized, all while keeping costs low?
Martin thinks we have to start from the fundamentals, especially when we are already late to the EMR game. He believes that we should first start by serving the needs of clinicians who continue to face burnout due to a growing amount of ancillary technology and administrative tasks.
In parallel, there needs to be a drastic reform in our healthcare payment policies to ensure providers are incentivized to integrate digital solutions into traditional clinical practices.
Closing the research-practice gap for clinicians
Having to deal with such high volumes of patients, particularly in primary care, physicians often have to quickly extrapolate from their experience to determine the best possible treatment for patients at the point of care. While there is nothing wrong with relying on experience, it is becoming extremely difficult to do with mounting expectations for physicians to constantly keep abreast of new research-proven treatments, and integrate novel clinical practices into their services.
We are certainly getting more health literate and better-informed with online access to loads of diagnostic and disease information at our fingertips. With wearables growing approximately 4% year over year and a user base of 3 million (2019) in Canada, there are clear indications that Canadians are becoming more health-conscious and are expecting their healthcare providers to be equally up-to-date and well-informed.
At the same time, policymakers like the European Commission and the World Health Organization (WHO) are putting heavier focus on patient empowerment in response to the rise of chronic diseases in world demographics—chronic diseases like cardiovascular disease, cancer, and diabetes attribute to an alarming 86% of deaths in Europe in 2017. Empowerment encourages patients to play a larger role in their treatment journey, working alongside their healthcare providers towards personalized and self-managed care. Digital solutions and services are seen as enablers in this shift from provider-driven to patient-centric care. Everything considered, there is an unavoidable need for clinicians to catch up with both technological and medical trends in order to satisfy growing demands.
Physicians, however, cannot possibly stay on top of all of today’s clinical and research trends especially with such rapid advances in genomics, precision medicine and other computation-powered research. It is also unrealistic for clinicians to have to manually and continuously modernize their workflow just to keep up. This is precisely where health tech firms like Think Research add value.
Think Research’s digital order sets, for instance, alleviate the burden of on-the-spot decision making by providing analytics-driven and evidence-based checklists that are designed by condition, disease or procedure. For instance, “when a patient is admitted for a kidney transplant, their medical tests, treatments and medications must occur in a specific order. Routine blood work and the administering of antibiotics and antiviral medications all require precise considerations for specific circumstances.” Order sets help streamline this process by delivering standardized guidelines for clinicians at the point of care.
Traditionally, it could take up to 17 years to translate medical knowledge into practice and for best practices to reach the point of care. Today, digital and data platforms allow a network of healthcare providers to collaboratively share insights from patient outcomes and local order set implementations. This accelerated the feedback loop of learnings that allowed for quicker iterations of order set improvements, ultimately, making treatments more accurate and comprehensive.
This type of data-fueled learning is still maturing and there is a ways to go to fully automate the clinical pathway for all disease types. Martin believes we might still be at least a decade away from AI intelligence that can serve this purpose, at least in the Canadian market.
Throwing virtual care into the mix
Federal and provincial governments are making more concrete investments to widen the reach of virtual services especially to rural and remote communities where physical access to health services is more difficult. In response to this push, there is a multitude of eVisit services (e.g. Maple) available today that offer patients self-paid and on-demand telemedicine services. Patients can easily select their symptoms, add past medical records, and quickly get 1-on-1 time with the next available doctor.
Though it definitely is a great step forward, Martin thinks this next-available pairing might not gel with the traditional doctor-patient relationship in the Ontario health care system. Ontarians are very much attached to their primary care physicians and have learned to rely on them for “illness prevention, health promotion, diagnosis, treatment, and rehabilitation and counselling”. In most cases, patients view their primary care physician as a personal expert of their medical history and a trusted advisor of their health and lifestyle decisions. With convenient virtual services in the mix, there is a need to find alternative ways to facilitate this connection between patients and their general practitioners (GPs). This is especially true for chronic care and mental health conditions where personal and long-term understanding of the patient and the patient’s family history play a critical part.
In contrast to the on-demand and next-available offering for treating low-maintenance conditions, some health tech companies offer providers a suite of virtual services across the “care continuum”—primary, acute, long term care—that foster long-term doctor-patient relationships. An example is Think Research’s multi-channel messaging platform which allows doctors to connect with multiple patients at the same time. It enables physicians to parallelize routine appointments like prescription renewals and referrals online while physically attending to patients.
Virtual care platforms not only streamline the physician workflow by alleviating administrative overhead (with eReferrals and digital progress notes), these systems also ensure that the utilization of the physician’s time is optimized between routine and monitoring services that can be virtualized, and high-touch services that require physical attention.
He thinks it is healthier to view virtual care technology as an enabler, increasing both access and quality of care, rather than another service that clinicians must juggle along with their current workload.
On top of which, virtual care is still new in Canada. The proposition of using mHealth, virtualization, and predictive analytics in areas like early detection and chronic disease management is still far from common. Today, data and analytics for and from virtual services are still very basic and largely focused on operational optimization, mostly activity-type data such as the number of patients visited. Martin is uncertain how impactful advanced analytics features would be at the moment. However, he believes the growing reach and expansion of virtual services (in home care and patient support programs) would open the gateway to new data dimensions and accelerate the growth of insight-rich data needed for advanced analytics.
Are our healthcare payment policies working against us?
It’s not always known to Ontarians, but GPs actually suffer monetary loss whenever a patient receives care outside of their clinic—in a nearby walk-in for instance. In fact, primary care physicians in Ontario traditionally operate under either a capitation-based or fee-for-service (FFS) payment model with added premiums based on the comprehensiveness of care offered to their roster of patients, such as after-hours services. In the case of walk-in’s, the province will have to compensate the walk-in doctor by clawing back these bonuses from the patient’s GP. Under these rigid payment policies, physicians can even choose to terminate care by de-rostering patients that often seek healthcare elsewhere.
Accounting for 21% of all health spending in Canada in 2016, physician remuneration is the second-largest source of public expenditures. Traditional capitation-based and FFS models had their fair share of drawbacks and are seen to be increasingly obsolete, especially with the rise of digital health and patient centricity. Bean counting mechanisms like FFS, for example, can be abused by prescribing an excessive amount of services which may not necessarily add value in terms of quality of care. It also encourages territorial behaviour among providers since clinicians can only bill for services they provide. Under capitation, there is running risk that physicians avoid complex cases, commonly seen in older patient groups, because they are not incentivized to take on the risk.
In the future world of digital-led and patient-first healthcare, some believe that a value-based remuneration model can help put quality of care and improved patient outcomes back in focus. Ontario healthcare policymakers have already begun the incremental shift to blended payment models in primary care. The blended capitation model, for instance, now takes into account the age and sex of the enrolled patient for a pre-set bundle of primary care services. There is also a monthly comprehensive-care capitation payment model to better incentivize chronic disease management programs. Despite this progress, there is still a lot of ambiguity on where and how digital health services fit within these models.
It may not be realistic yet for drastic reform towards value-based and pay-for-performance structures as the industry continues the debate on what ‘value’ actually means. University of Utah Health’s “The State of Value in U.S. Health Care” survey in 2018 revealed that there are still diverging definitions of ‘value’ across quality, service, and cost depending on who is setting the agenda—patients, physicians, employers who provide medical benefits, etc.
Martin believes it is a fundamental problem that warrants heavy and long-term attention from policymakers, especially as digital offerings for both consumers and healthcare providers continue its ascending growth.
Featured Company & Expert
Think Research is a Toronto-based company that offers a number of clinical tools that connect patients and clinicians to each other while bringing best practices at the point of care.
Want to learn more about digital health & the concept of Analytics for Good?
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